<?xml version="1.0" encoding="UTF-8"?>
<quiz>
<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L57- Multiplication and Division Inequalities</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360810  -->
  <question type="formulas">
    <name>
      <text>L57- solve-graph Division inequalities</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[{ques}
Solve for {name}, then graph the solution.<br><br>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[number1={3:8:1};
ans={0,1,2,3};
choices=shuffle([0,1,2,3]);
name={"A","B","C","D","E","F","G","H","R","S","T","X","Y","Z"};
offset={4:9:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number2=number1+1;
a=choices[0];
b=choices[1];
c=choices[2];
d=choices[3];
ques=join("",name,"÷",offset," ",pick(ans,"&lt;",">","≤","≥")," ",number1/offset);
mcChoices=["a","b","c","d"];
selection = (choices[0]==ans)?0:-1;
selection = (choices[1]==ans)?1:selection;
selection = (choices[2]==ans)?2:selection;
selection = (choices[3]==ans)?3:selection;
letterAns=mcChoices[selection];
feedback=pick(ans,"Less than (&lt;) means to include the numbers with a lower value.  Do not include the value of the number.","Greater than (>) means include the numbers of higher value.  Do not include the value of the number.","Less than or equal to (≤) means to include the number and all numbers that are a smaller value.","Greater than or equal to (≥) means include the number and all numbers of larger value.");
ineq=["&lt;",">","≤","≥"];
FBp1=pick(ans,"less than","greater than","less than","greater than");
test=pick(ans,number1-1,number1+1,number1-1,number1+1);]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[ans,number1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">The solution to the inequality is {name} {_0:ineq:MCE} {_1}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"><br></p>
<table><tbody><tr><td><p dir="ltr">{name}÷{offset}&nbsp; {=ineq[ans]} {=number1/offset}</p>
          </td><td></td>
            <td>&nbsp; Given</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">&nbsp; <span class="" style="color: rgb(255, 51, 102);">x {offset}</span>&nbsp; &nbsp; &nbsp; <span class="" style="color: rgb(255, 51, 102);">x{offset}</span></p>
            </td><td></td>
            <td>Multiply both sides by&nbsp;<span class="" style="color: rgb(255, 51, 102);">{offset}</span></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr"><strong>{name}&nbsp; {=ineq[ans]} {number1}</strong></p>
            </td><td></td>
            <td>Simplify</td>
        </tr>
        <tr>
            <td colspan="2">
                <h3 style="text-align: left;"><strong><span class="" style="color: rgb(51, 102, 255);">Check the answer</span></strong></h3>
            </td>

        </tr>
        <tr>
            <td>
                <p dir="ltr">{name}÷{offset} {=ineq[ans]} {=number1/offset}<br></p>
            </td><td></td>
            <td>Given</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr"><span class="" style="color: rgb(255, 51, 102);">({test})<span class="" style="color: rgb(51, 51, 51);">÷({offset})</span></span>&nbsp;{=ineq[ans]} {=number1/offset}<br></p>
            </td><td></td>
            <td>The inequality is {=ineq[ans]} so <br>choose a number {FBp1} {number1}.<br>In the example I will use <span class="" style="color: rgb(255, 51, 102);">{test}</span> as your substitution.</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">{=test/offset} {=ineq[ans]} {=number1/offset}<br></p>
            </td><td></td>
            <td>Simplify<br>Since it is a <strong>true </strong>statement, <br>the solution is correct.</td>
        </tr>
       
    </tbody>
</table>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>selection</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>choices[_0]==ans</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[Graph the solution of {ques} for the set of Real Numbers.<table>
    <tbody>
        <tr><td>{_0:mcChoices}<br><br><br></td>
            <td>
                <jsxgraph width="500" height="300">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,22,11,-10], axis:false, ShowCopyright: false, showNavigation:false});
                    let A={a};
                    let B={b};
                    let C={c};
                    let D={d};

                    var numLine = board.create('axis', [[0, 18],[10, 18]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (A===0){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (A===1){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (A===2){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (A===3){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,18.5,"(a)"],{fontSize:15});

                    var numLine = board.create('axis', [[0, 12],[10, 12]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (B===0){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (B===1){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (B===2){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (B===3){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,12.5,"(b)"],{fontSize:15});



                    var numLine = board.create('axis', [[0, 6],[10, 6]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (C===0){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (C===1){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (C===2){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (C===3){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,6.5,"(c)"],{fontSize:15});


                    var numLine = board.create('axis', [[0, 0],[10, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (D===0){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (D===1){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (D===2){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (D===3){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,0.5,"(d)"],{fontSize:15});
                </jsxgraph>
            </td>
            
        </tr>
    </tbody>
</table>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[{feedback}

The correct graph is:
<jsxgraph width="500" height="100">
    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,5,11,-10], axis:false, ShowCopyright: false, showNavigation:false}); let A={ans}; var numLine = board.create('axis', [[0, 0],[10, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}}); if (A===0){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:3}); var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'}); var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } else if (A===1){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""}); var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'}); var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } else if (A===2){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""}); var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } else if (A===3){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""}); var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } var tA=board.create('text',[-.7,0.5,"({letterAns})"],{fontSize:15});
</jsxgraph>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360809  -->
  <question type="formulas">
    <name>
      <text>L57- solve-graph Multiplication inequalities</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[{ques}
Solve for {name}, then graph the solution.<br><br>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[number1={3:8:1};
ans={0,1,2,3};
choices=shuffle([0,1,2,3]);
name={"A","B","C","D","E","F","G","H","R","S","T","X","Y","Z"};
offset={4:9:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number2=number1+1;
a=choices[0];
b=choices[1];
c=choices[2];
d=choices[3];
ques=join("",offset,name," ",pick(ans,"&lt;",">","≤","≥")," ",number1*offset);
mcChoices=["a","b","c","d"];
selection = (choices[0]==ans)?0:-1;
selection = (choices[1]==ans)?1:selection;
selection = (choices[2]==ans)?2:selection;
selection = (choices[3]==ans)?3:selection;
letterAns=mcChoices[selection];
feedback=pick(ans,"Less than (&lt;) means to include the numbers with a lower value.  Do not include the value of the number.","Greater than (>) means include the numbers of higher value.  Do not include the value of the number.","Less than or equal to (≤) means to include the number and all numbers that are a smaller value.","Greater than or equal to (≥) means include the number and all numbers of larger value.");
ineq=["&lt;",">","≤","≥"];
FBp1=pick(ans,"less than","greater than","less than","greater than");
test=pick(ans,number1-1,number1+1,number1-1,number1+1);]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[ans,number1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">The solution to the inequality is {name} {_0:ineq:MCE} {_1}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"><br></p>
<table>
    <tbody>
        <tr>
            <td>
                <p dir="ltr">{offset}{name}&nbsp; {=ineq[ans]} {=number1*offset}</p>
          </td><td></td>
            <td>&nbsp; Given</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">&nbsp; <span class="" style="color: rgb(255, 51, 102);">÷ {offset}</span>&nbsp; &nbsp; &nbsp; <span class="" style="color: rgb(255, 51, 102);">÷{offset}</span></p>
            </td><td></td>
            <td>Divide both sides by&nbsp;<span class="" style="color: rgb(255, 51, 102);">{offset}</span></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr"><strong>{name}&nbsp; {=ineq[ans]} {number1}</strong></p>
            </td><td></td>
            <td>Simplify</td>
        </tr>
        <tr>
            <td colspan="2">
                <h3 style="text-align: left;"><strong><span class="" style="color: rgb(51, 102, 255);">Check the answer</span></strong></h3>
            </td>

        </tr>
        <tr>
            <td>
                <p dir="ltr">{offset}{name} {=ineq[ans]} {=number1*offset}<br></p>
            </td><td></td>
            <td>Given</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr"><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 51, 51);">({offset})</span>({test})</span>&nbsp;{=ineq[ans]} {=number1*offset}<br></p>
            </td><td></td>
            <td>The inequality is {=ineq[ans]} so <br>choose a number {FBp1} {number1}.<br>In the example I will use <span class="" style="color: rgb(255, 51, 102);">{test}</span> as your substitution.</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">{=test*offset} {=ineq[ans]} {=number1*offset}<br></p>
            </td><td></td>
            <td>Simplify<br>Since it is a <strong>true </strong>statement, <br>the solution is correct.</td>
        </tr>
       
    </tbody>
</table>]]></text>
 </feedback>
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<text></text>
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<text></text>
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 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
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  <text>selection</text>
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  <text>choices[_0]==ans</text>
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 <subqtext format="html">
<text><![CDATA[Graph the solution of {ques} for the set of Real Numbers.<table>
    <tbody>
        <tr><td>{_0:mcChoices}<br><br><br></td>
            <td>
                <jsxgraph width="500" height="300">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,22,11,-10], axis:false, ShowCopyright: false, showNavigation:false});
                    let A={a};
                    let B={b};
                    let C={c};
                    let D={d};

                    var numLine = board.create('axis', [[0, 18],[10, 18]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (A===0){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (A===1){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (A===2){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (A===3){
                    var pA1=board.create('point',[{number1},18],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,18],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,18.5,"(a)"],{fontSize:15});

                    var numLine = board.create('axis', [[0, 12],[10, 12]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (B===0){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (B===1){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (B===2){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (B===3){
                    var pA1=board.create('point',[{number1},12],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,12],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,12.5,"(b)"],{fontSize:15});



                    var numLine = board.create('axis', [[0, 6],[10, 6]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (C===0){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (C===1){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (C===2){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (C===3){
                    var pA1=board.create('point',[{number1},6],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,6],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,6.5,"(c)"],{fontSize:15});


                    var numLine = board.create('axis', [[0, 0],[10, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});


                    if (D===0){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:3});
                    var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (D===1){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""});
                    var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'});
                    var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (D===2){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    } else if (D===3){
                    var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""});

                    var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0});
                    var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'});
                    }
                    var tA=board.create('text',[-.7,0.5,"(d)"],{fontSize:15});
                </jsxgraph>
            </td>
            
        </tr>
    </tbody>
</table>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[{feedback}

The correct graph is:
<jsxgraph width="500" height="100">
    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,5,11,-10], axis:false, ShowCopyright: false, showNavigation:false}); let A={ans}; var numLine = board.create('axis', [[0, 0],[10, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 0,minorTicks: 1,tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}}); if (A===0){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:3}); var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'}); var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } else if (A===1){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""}); var pA1w=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:"",size:1,strokeColor:'#FFFFFF',fillColor:'#FFFFFF'}); var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } else if (A===2){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""}); var pA0=board.create('point',[0,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } else if (A===3){ var pA1=board.create('point',[{number1},0],{fixed:true,showInfobox:false,name:""}); var pA0=board.create('point',[10,0],{fixed:true,showInfobox:false,name:"",size:0}); var l1=board.create('line',[pA1,pA0],{firstArrow:false,lastArrow:true,straightFirst:false,straightLast:false,strokeColor:'#FF0000'}); } var tA=board.create('text',[-.7,0.5,"({letterAns})"],{fontSize:15});
</jsxgraph>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L58 - The area of a trapezoid</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360857  -->
  <question type="formulas">
    <name>
      <text>L58  areaTrapezoid</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xa},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var lheight=board.create('line',[p1,ph],{strokeColor:'{color2}',dash:2,straightFirst:false,straightLast:false});
    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
    var lineRt1=board.create('line',[[{xa},{yc}+.5],[{xa}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var lineRt2=board.create('line',[[{xa}+.5,{yc}],[{xa}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAC} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15,fixed:true});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,fixed:true});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"></p><div><p dir="ltr">Area of a Trapezoid:&nbsp; &nbsp;\(\frac{1}{2}\)h(a+b)</p><p dir="ltr">base a = {baseA}</p><p dir="ltr">base b={baseB}</p><p dir="ltr">height={height}</p></div><table><tbody><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)h(a+b)</p></td><td>&nbsp; &nbsp; &nbsp; &nbsp;</td><td>given</td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({baseA}+{baseB})</p></td><td></td><td>Substitute the known values<br><div>base a = {baseA}<br>base b={baseB}<br>height={height}</div><div><br></div></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({=baseA+baseB})</p></td><td></td><td>Simplify inside parentheses.<br>{baseA}+{baseB} =&nbsp;{=baseA+baseB}<br><br></td></tr><tr><td><p dir="ltr">Area =(\(\frac{1}{2}\))({=height*(baseA+baseB)})</p></td><td></td><td>Since only multiplication is left, use the associative property to multiply {height} times&nbsp;&nbsp;{=baseA+baseB} = {=height*(baseA+baseB)}<br><br></td></tr><tr><td><p dir="ltr">Area (\(\frac{1}{2}\))(\(\frac{{=height*(baseA+baseB)}}{1}\))</p></td><td></td><td>To multiply a whole number by a fraction write a 1 in the denominator of the whole number.<br>{=height*(baseA+baseB)}= \(\frac{{=height*(baseA+baseB)}}{1}\)<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{{=2*area}}{2}\)</p></td><td></td><td>Multiply the numerators, multiply the denominators.<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;{area}</p></td><td></td><td>Divide the numerator by 2.&nbsp; &nbsp;&nbsp;{=2*area}&nbsp;÷ 2 = {area}<br><br></td></tr></tbody></table><br><br><p></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={3:5:1};
ya={6:10:1};
xb={6:8:1};
xc={0:2:1};
yc={1:4:1};
xd={9:11:1};

#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=xb-xa;
baseB=xd-xc;
height=ya-yc;
area=.5*height*(baseA+baseB);
midX=xa;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2);
sideBD=round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2);
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
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  <text></text>
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 <answermark>
  <text>1</text>
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 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[area,1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
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 <postunit>
  <text></text>
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  <text>1</text>
 </ruleid>
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  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[Calculate the area of the trapezoid.<br><table>
    <tbody>
        <tr>
            <td>Area= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table><script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
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        var txt = $(".formulas_number").val();
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</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
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  </question>

<!-- question: 360856  -->
  <question type="formulas">
    <name>
      <text>L58 - Area Trapezoid 3</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[&nbsp;<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
            var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
            var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
            var p4=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
            var p3=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
            var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});

            var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});

            var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
            var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});

            var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAD} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
            var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBC} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
        </jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr" style="text-align: left;"></p>
    <p dir="ltr">Area of a Trapezoid:&nbsp; &nbsp;\(\frac{1}{2}\)h(a+b)</p>
    <p dir="ltr">base a = {baseA}</p>
    <p dir="ltr">base b={baseB}</p>
    <p dir="ltr">height={height}</p>

</div>
<table>
    <tbody>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)h(a+b)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp;</td>
            <td>given</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({baseA}+{baseB})</p>
            </td>
            <td></td>
            <td>Substitute the known values<br><div class="editor-indent" style="margin-left: 30px;">
                base a = {baseA}<br>
                base b={baseB}<br>
                height={height}</div><div class="editor-indent" style="margin-left: 30px;"><br></div>
            </td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({=baseA+baseB})</p>
            </td>
            <td></td>
            <td>Simplify inside parentheses.<br>{baseA}+{baseB} =&nbsp;{=baseA+baseB}<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =(\(\frac{1}{2}\))({=height*(baseA+baseB)})</p>
            </td>
            <td></td>
            <td>Since only multiplication is left, use the associative property to multiply {height} times&nbsp;&nbsp;{=baseA+baseB} = {=height*(baseA+baseB)}<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area (\(\frac{1}{2}\))(\(\frac{{=height*(baseA+baseB)}}{1}\))</p>
            </td>
            <td></td>
            <td>To multiply a whole number by a fraction write a 1 in the denominator of the whole number.<br>{=height*(baseA+baseB)}= \(\frac{{=height*(baseA+baseB)}}{1}\)<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{{=2*area}}{2}\)</p>
            </td>
            <td></td>
            <td>Multiply the numerators, multiply the denominators.<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;{area}</p>
            </td>
            <td></td>
            <td>Divide the numerator by 2.&nbsp; &nbsp;&nbsp;{=2*area}&nbsp;÷ 2 = {area}<br><br></td>
        </tr>
    </tbody>
</table>]]></text>
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</file>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={0:2:1};
ya={6:10:1};
xc={3:5:1};
yc={1:4:1};
xb={9:11:1};
factor={10:100};
#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[factor=1;
xd=xa;
yb=ya;
yd=yc;
baseA=(xb-xa)*factor;
baseB=(xc-xd)*factor;
height=(ya-yd)*factor;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAD=(round(sqrt(pow(xa-xd,2)+pow(ya-yd,2)),2))*factor;
sideBC=(round(sqrt(pow(xb-xc,2)+pow(yb-yc,2)),2))*factor;
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAD+sideBC;]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[area,1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[Calculate the area of the trapezoid.<br><table><tbody><tr><td>Area= {_0}</td><td>{_1:units}</td></tr></tbody></table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360859  -->
  <question type="formulas">
    <name>
      <text>L58 - Perimeter Trapezoid 3</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});

    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});

    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});

    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAD} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBC} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"><p dir="ltr" style="text-align: left;"></p><p dir="ltr"><span>Perimeter is the distance around a figure.</span><br></p><p dir="ltr">The perimeter of a trapezoid is the sum of the sides.</p><p dir="ltr">perimeter= {baseA} + {sideBD} + {baseB} + {sideAC}</p><p dir="ltr">perimeter = {perimeter}&nbsp;{unit}</p><p dir="ltr">The units are {unit} because distance is measured on a ruler.</p><br><br><p></p></div>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={0:2:1};
ya={6:10:1};
xc={3:5:1};
yc={1:4:1};
xb={9:11:1};
factor={10:100};
#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[factor=1;
xd=xa;
yb=ya;
yd=yc;
baseA=(xb-xa)*factor;
baseB=(xc-xd)*factor;
height=(ya-yd)*factor;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAD=(round(sqrt(pow(xa-xd,2)+pow(ya-yd,2)),2))*factor;
sideBC=(round(sqrt(pow(xb-xc,2)+pow(yb-yc,2)),2))*factor;
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAD+sideBC;]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[perimeter,0]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table>
    <tbody>
        <tr>
            <td>Perimeter= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360860  -->
  <question type="formulas">
    <name>
      <text>L58 Perimeter Trapezoid</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xa},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var lheight=board.create('line',[p1,ph],{strokeColor:'{color2}',dash:2,straightFirst:false,straightLast:false});
    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
    var lineRt1=board.create('line',[[{xa},{yc}+.5],[{xa}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var lineRt2=board.create('line',[[{xa}+.5,{yc}],[{xa}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAC} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15,fixed:true});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,fixed:true});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Perimeter is the distance around a figure.</p><p dir="ltr" style="text-align: left;">The perimeter of a trapezoid is the sum of the sides.</p><p dir="ltr" style="text-align: left;">perimeter= {baseA} + {sideBD} + {baseB} + {sideAC}</p><p dir="ltr" style="text-align: left;">perimeter = {perimeter} <span class="" style="color: rgb(51, 102, 255);">{unit}</span></p><p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(51, 102, 255);">The units are {unit} because distance is measured on a ruler.</span></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={3:5:1};
ya={6:10:1};
xb={6:8:1};
xc={0:2:1};
yc={1:4:1};
xd={9:11:1};

#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=xb-xa;
baseB=xd-xc;
height=ya-yc;
area=.5*height*(baseA+baseB);
midX=xa;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2);
sideBD=round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2);
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[perimeter,0]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[Calculate the perimeter of the trapezoid.<br><table>
    <tbody>
        <tr>
            <td>Perimeter= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table><script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360858  -->
  <question type="formulas">
    <name>
      <text>L58-area trapezoid2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var lheight=board.create('line',[p4,ph],{strokeColor:'{color2}',dash:2,straightFirst:false,straightLast:false,fixed:true});
    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
    var lineRt1=board.create('line',[[{xc},{yc}+.5],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var lineRt1=board.create('line',[[{xc}+.5,{yc}],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAC} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"><p dir="ltr" style="text-align: left;"></p><p dir="ltr"><span style="font-size: 0.9375rem;"></span></p><div><p dir="ltr">Area of a Trapezoid:&nbsp; &nbsp;\(\frac{1}{2}\)h(a+b)</p><p dir="ltr">base a = {baseA}</p><p dir="ltr">base b={baseB}</p><p dir="ltr">height={height}</p></div><table><tbody><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)h(a+b)</p></td><td>&nbsp; &nbsp; &nbsp; &nbsp;</td><td>given</td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({baseA}+{baseB})</p></td><td></td><td>Substitute the known values<br><div>base a = {baseA}<br>base b={baseB}<br>height={height}</div><div><br></div></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({=baseA+baseB})</p></td><td></td><td>Simplify inside parentheses.<br>{baseA}+{baseB} =&nbsp;{=baseA+baseB}<br><br></td></tr><tr><td><p dir="ltr">Area =(\(\frac{1}{2}\))({=height*(baseA+baseB)})</p></td><td></td><td>Since only multiplication is left, use the associative property to multiply {height} times&nbsp;&nbsp;{=baseA+baseB} = {=height*(baseA+baseB)}<br><br></td></tr><tr><td><p dir="ltr">Area (\(\frac{1}{2}\))(\(\frac{{=height*(baseA+baseB)}}{1}\))</p></td><td></td><td>To multiply a whole number by a fraction write a 1 in the denominator of the whole number.<br>{=height*(baseA+baseB)}= \(\frac{{=height*(baseA+baseB)}}{1}\)<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{{=2*area}}{2}\)</p></td><td></td><td>Multiply the numerators, multiply the denominators.<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;{area}</p></td><td></td><td>Divide the numerator by 2.&nbsp; &nbsp;&nbsp;{=2*area}&nbsp;÷ 2 = {area}<br><br></td></tr></tbody></table><br><p></p></div>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xc={3:5:1};
ya={6:10:1};
xd={6:8:1};
xa={0:2:1};
yc={1:4:1};
xb={9:11:1};

#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=xb-xa;
baseB=xd-xc;
height=ya-yc;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2);
sideBD=round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2);
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[area,1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[Calculate the area of the trapezoid.<br><table>
    <tbody>
        <tr>
            <td>Area= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360861  -->
  <question type="formulas">
    <name>
      <text>L58-trapezoid2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var lheight=board.create('line',[p4,ph],{strokeColor:'{color2}',dash:2,straightFirst:false,straightLast:false,fixed:true});
    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
    var lineRt1=board.create('line',[[{xc},{yc}+.5],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var lineRt1=board.create('line',[[{xc}+.5,{yc}],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAC} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"><p dir="ltr" style="text-align: left;"></p><p dir="ltr"><span style="font-size: 0.9375rem;">Perimeter is the distance around a figure.</span><br></p><p dir="ltr">The perimeter of a trapezoid is the sum of the sides.</p><p dir="ltr">perimeter= {baseA} + {sideBD} + {baseB} + {sideAC}</p><p dir="ltr">perimeter = {perimeter}&nbsp;{unit}</p><p dir="ltr">The units are {unit} because distance is measured on a ruler.</p><br><p></p></div>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xc={3:5:1};
ya={6:10:1};
xd={6:8:1};
xa={0:2:1};
yc={1:4:1};
xb={9:11:1};

#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=xb-xa;
baseB=xd-xc;
height=ya-yc;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2);
sideBD=round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2);
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text><![CDATA[<table>
    <tbody>
        <tr>
            <td>Perimeter= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
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<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L58 - The area of a trapezoid/L58- Trapezoid-Area</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360891  -->
  <question type="formulas">
    <name>
      <text>L58  areaTrapezoid</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xa},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var lheight=board.create('line',[p1,ph],{strokeColor:'{color2}',dash:2,straightFirst:false,straightLast:false});
    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
    var lineRt1=board.create('line',[[{xa},{yc}+.5],[{xa}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var lineRt2=board.create('line',[[{xa}+.5,{yc}],[{xa}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAC} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15,fixed:true});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,fixed:true});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"></p><div><p dir="ltr">Area of a Trapezoid:&nbsp; &nbsp;\(\frac{1}{2}\)h(a+b)</p><p dir="ltr">base a = {baseA}</p><p dir="ltr">base b={baseB}</p><p dir="ltr">height={height}</p></div><table><tbody><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)h(a+b)</p></td><td>&nbsp; &nbsp; &nbsp; &nbsp;</td><td>given</td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({baseA}+{baseB})</p></td><td></td><td>Substitute the known values<br><div>base a = {baseA}<br>base b={baseB}<br>height={height}</div><div><br></div></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({=baseA+baseB})</p></td><td></td><td>Simplify inside parentheses.<br>{baseA}+{baseB} =&nbsp;{=baseA+baseB}<br><br></td></tr><tr><td><p dir="ltr">Area =(\(\frac{1}{2}\))({=height*(baseA+baseB)})</p></td><td></td><td>Since only multiplication is left, use the associative property to multiply {height} times&nbsp;&nbsp;{=baseA+baseB} = {=height*(baseA+baseB)}<br><br></td></tr><tr><td><p dir="ltr">Area (\(\frac{1}{2}\))(\(\frac{{=height*(baseA+baseB)}}{1}\))</p></td><td></td><td>To multiply a whole number by a fraction write a 1 in the denominator of the whole number.<br>{=height*(baseA+baseB)}= \(\frac{{=height*(baseA+baseB)}}{1}\)<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{{=2*area}}{2}\)</p></td><td></td><td>Multiply the numerators, multiply the denominators.<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;{area}</p></td><td></td><td>Divide the numerator by 2.&nbsp; &nbsp;&nbsp;{=2*area}&nbsp;÷ 2 = {area}<br><br></td></tr></tbody></table><br><br><p></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={3:5:1};
ya={6:10:1};
xb={6:8:1};
xc={0:2:1};
yc={1:4:1};
xd={9:11:1};
factor={1:20:1};
#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=factor*(xb-xa);
baseB=factor*(xd-xc);
height=factor*(ya-yc);
area=.5*height*(baseA+baseB);
midX=xa;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=factor*(round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2));
sideBD=factor*(round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2));
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
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  <text>1</text>
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 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[area,1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
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  <text>1</text>
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  <text></text>
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 <subqtext format="html">
<text><![CDATA[Calculate the area of the trapezoid.<br><table>
    <tbody>
        <tr>
            <td>Area= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table><script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360890  -->
  <question type="formulas">
    <name>
      <text>L58 - Area Trapezoid 3</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[&nbsp;<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
            var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
            var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
            var p4=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
            var p3=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
            var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});

            var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});

            var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
            var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});

            var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAD} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
            var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBC} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
        </jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr" style="text-align: left;"></p>
    <p dir="ltr">Area of a Trapezoid:&nbsp; &nbsp;\(\frac{1}{2}\)h(a+b)</p>
    <p dir="ltr">base a = {baseA}</p>
    <p dir="ltr">base b={baseB}</p>
    <p dir="ltr">height={height}</p>

</div>
<table>
    <tbody>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)h(a+b)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp;</td>
            <td>given</td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({baseA}+{baseB})</p>
            </td>
            <td></td>
            <td>Substitute the known values<br><div class="editor-indent" style="margin-left: 30px;">
                base a = {baseA}<br>
                base b={baseB}<br>
                height={height}</div><div class="editor-indent" style="margin-left: 30px;"><br></div>
            </td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({=baseA+baseB})</p>
            </td>
            <td></td>
            <td>Simplify inside parentheses.<br>{baseA}+{baseB} =&nbsp;{=baseA+baseB}<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =(\(\frac{1}{2}\))({=height*(baseA+baseB)})</p>
            </td>
            <td></td>
            <td>Since only multiplication is left, use the associative property to multiply {height} times&nbsp;&nbsp;{=baseA+baseB} = {=height*(baseA+baseB)}<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area (\(\frac{1}{2}\))(\(\frac{{=height*(baseA+baseB)}}{1}\))</p>
            </td>
            <td></td>
            <td>To multiply a whole number by a fraction write a 1 in the denominator of the whole number.<br>{=height*(baseA+baseB)}= \(\frac{{=height*(baseA+baseB)}}{1}\)<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;\(\frac{{=2*area}}{2}\)</p>
            </td>
            <td></td>
            <td>Multiply the numerators, multiply the denominators.<br><br></td>
        </tr>
        <tr>
            <td>
                <p dir="ltr">Area =&nbsp;{area}</p>
            </td>
            <td></td>
            <td>Divide the numerator by 2.&nbsp; &nbsp;&nbsp;{=2*area}&nbsp;÷ 2 = {area}<br><br></td>
        </tr>
    </tbody>
</table>]]></text>
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</file>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={0:2:1};
ya={6:10:1};
xc={3:5:1};
yc={1:4:1};
xb={9:11:1};
factor={10:100};
#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[factor=1;
xd=xa;
yb=ya;
yd=yc;
baseA=(xb-xa)*factor;
baseB=(xc-xd)*factor;
height=(ya-yd)*factor;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAD=(round(sqrt(pow(xa-xd,2)+pow(ya-yd,2)),2))*factor;
sideBC=(round(sqrt(pow(xb-xc,2)+pow(yb-yc,2)),2))*factor;
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAD+sideBC;]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[area,1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[Calculate the area of the trapezoid.<br><table><tbody><tr><td>Area= {_0}</td><td>{_1:units}</td></tr></tbody></table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360892  -->
  <question type="formulas">
    <name>
      <text>L58-area trapezoid2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var lheight=board.create('line',[p4,ph],{strokeColor:'{color2}',dash:2,straightFirst:false,straightLast:false,fixed:true});
    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
    var lineRt1=board.create('line',[[{xc},{yc}+.5],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var lineRt1=board.create('line',[[{xc}+.5,{yc}],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAC} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"><p dir="ltr" style="text-align: left;"></p><p dir="ltr"><span style="font-size: 0.9375rem;"></span></p><div><p dir="ltr">Area of a Trapezoid:&nbsp; &nbsp;\(\frac{1}{2}\)h(a+b)</p><p dir="ltr">base a = {baseA}</p><p dir="ltr">base b={baseB}</p><p dir="ltr">height={height}</p></div><table><tbody><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)h(a+b)</p></td><td>&nbsp; &nbsp; &nbsp; &nbsp;</td><td>given</td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({baseA}+{baseB})</p></td><td></td><td>Substitute the known values<br><div>base a = {baseA}<br>base b={baseB}<br>height={height}</div><div><br></div></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{1}{2}\)({height})({=baseA+baseB})</p></td><td></td><td>Simplify inside parentheses.<br>{baseA}+{baseB} =&nbsp;{=baseA+baseB}<br><br></td></tr><tr><td><p dir="ltr">Area =(\(\frac{1}{2}\))({=height*(baseA+baseB)})</p></td><td></td><td>Since only multiplication is left, use the associative property to multiply {height} times&nbsp;&nbsp;{=baseA+baseB} = {=height*(baseA+baseB)}<br><br></td></tr><tr><td><p dir="ltr">Area (\(\frac{1}{2}\))(\(\frac{{=height*(baseA+baseB)}}{1}\))</p></td><td></td><td>To multiply a whole number by a fraction write a 1 in the denominator of the whole number.<br>{=height*(baseA+baseB)}= \(\frac{{=height*(baseA+baseB)}}{1}\)<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;\(\frac{{=2*area}}{2}\)</p></td><td></td><td>Multiply the numerators, multiply the denominators.<br><br></td></tr><tr><td><p dir="ltr">Area =&nbsp;{area}</p></td><td></td><td>Divide the numerator by 2.&nbsp; &nbsp;&nbsp;{=2*area}&nbsp;÷ 2 = {area}<br><br></td></tr></tbody></table><br><p></p></div>]]></text>
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    <shownumcorrect/>
<varsrandom><text><![CDATA[xc={3:5:1};
ya={6:10:1};
xd={6:8:1};
xa={0:2:1};
yc={1:4:1};
xb={9:11:1};

#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=xb-xa;
baseB=xd-xc;
height=ya-yc;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2);
sideBD=round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2);
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
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<answernumbering><text>abc</text>
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<text><![CDATA[Calculate the area of the trapezoid.<br><table>
    <tbody>
        <tr>
            <td>Area= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
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        var family = $(".formulas_number").css('font-family');
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        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
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            $(".formulas_number").width(defaultWidth);
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<text></text>
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<text></text>
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<text></text>
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 <incorrectfeedback format="html">
<text></text>
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</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L58 - The area of a trapezoid/L58- Trapezoid - Perimeter</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360899  -->
  <question type="formulas">
    <name>
      <text>L58 - Perimeter Trapezoid 3</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
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    var p3=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});

    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});

    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});

    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAD} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBC} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
</jsxgraph>]]></text>
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    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"><p dir="ltr" style="text-align: left;"></p><p dir="ltr"><span>Perimeter is the distance around a figure.</span><br></p><p dir="ltr">The perimeter of a trapezoid is the sum of the sides.</p><p dir="ltr">perimeter= {baseA} + {sideBD} + {baseB} + {sideAC}</p><p dir="ltr">perimeter = {perimeter}&nbsp;{unit}</p><p dir="ltr">The units are {unit} because distance is measured on a ruler.</p><br><br><p></p></div>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={0:2:1};
ya={6:10:1};
xc={3:5:1};
yc={1:4:1};
xb={9:11:1};
factor={10:100};
#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[factor=1;
xd=xa;
yb=ya;
yd=yc;
baseA=(xb-xa)*factor;
baseB=(xc-xd)*factor;
height=(ya-yd)*factor;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAD=(round(sqrt(pow(xa-xd,2)+pow(ya-yd,2)),2))*factor;
sideBC=(round(sqrt(pow(xb-xc,2)+pow(yb-yc,2)),2))*factor;
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAD+sideBC;]]></text>
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<answernumbering><text>none</text>
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  <text></text>
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  <text><![CDATA[_err < 0.01]]></text>
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<text><![CDATA[<table>
    <tbody>
        <tr>
            <td>Perimeter= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
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                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
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    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
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        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
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 <feedback format="html">
<text></text>
 </feedback>
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<text></text>
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<text></text>
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 <incorrectfeedback format="html">
<text></text>
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</answers>
  </question>

<!-- question: 360900  -->
  <question type="formulas">
    <name>
      <text>L58 Perimeter Trapezoid</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xa},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
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    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
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    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,fixed:true});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Perimeter is the distance around a figure.</p><p dir="ltr" style="text-align: left;">The perimeter of a trapezoid is the sum of the sides.</p><p dir="ltr" style="text-align: left;">perimeter= {baseA} + {sideBD} + {baseB} + {sideAC}</p><p dir="ltr" style="text-align: left;">perimeter = {perimeter} <span class="" style="color: rgb(51, 102, 255);">{unit}</span></p><p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(51, 102, 255);">The units are {unit} because distance is measured on a ruler.</span></p>]]></text>
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    <penalty>0.3333333</penalty>
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    <idnumber></idnumber>
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      <text>Your answer is correct.</text>
    </correctfeedback>
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      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xa={3:5:1};
ya={6:10:1};
xb={6:8:1};
xc={0:2:1};
yc={1:4:1};
xd={9:11:1};

#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=xb-xa;
baseB=xd-xc;
height=ya-yc;
area=.5*height*(baseA+baseB);
midX=xa;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2);
sideBD=round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2);
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text><![CDATA[Calculate the perimeter of the trapezoid.<br><table>
    <tbody>
        <tr>
            <td>Perimeter= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table><script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
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    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
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        var family = $(".formulas_number").css('font-family');
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        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
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        if (actualWidth >= checkWidth) {
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</script>]]></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 360901  -->
  <question type="formulas">
    <name>
      <text>L58-trapezoid2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="300" height="300">var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,12,12,-1], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{xa},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var p2=board.create('point',[{xb},{yb}],{size:0,name:'',showInfobox:false,fixed:true});
    var p3=board.create('point',[{xd},{yd}],{size:0,name:'',showInfobox:false,fixed:true});
    var p4=board.create('point',[{xc},{yc}],{size:0,name:'',showInfobox:false,fixed:true});
    var ph=board.create('point',[{xc},{ya}],{size:0,name:'',showInfobox:false,fixed:true});
    var lheight=board.create('line',[p4,ph],{strokeColor:'{color2}',dash:2,straightFirst:false,straightLast:false,fixed:true});
    var rect=board.create('polygon',[p1,p2,p3,p4],{fillColor:'{color1}'});
    var theight=board.create('text',[{midX}+.25,{midY},"{height} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15,color:'{color2}',fixed:true});
    var tbasea=board.create('text',[.5*({xb}+{xa}),{ya}+.25,"{baseA} {unit}"],{anchorX:'middle',anchorY:'bottom',fontSize:15,fixed:true});
    var tbaseb=board.create('text',[.5*({xc}+{xd}),{yc}-.25,"{baseB} {unit}"],{anchorX:'middle',anchorY:'top',fontSize:15,fixed:true});
    var lineRt1=board.create('line',[[{xc},{yc}+.5],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var lineRt1=board.create('line',[[{xc}+.5,{yc}],[{xc}+.5,{yc}+.5]],{strokeColor:'{color2}',straightFirst:false,straightLast:false,fixed:true});
    var tsideAC=board.create('text',[.5*({xc}+{xa}),.5*({ya}+{yc}),"{sideAC} {unit}"],{anchorX:'right',anchorY:'center',fontSize:15});
    var tsideBD=board.create('text',[.5*({xb}+{xd}),.5*({yb}+{yd}),"{sideBD} {unit}"],{anchorX:'left',anchorY:'center',fontSize:15});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"><p dir="ltr" style="text-align: left;"></p><p dir="ltr"><span style="font-size: 0.9375rem;">Perimeter is the distance around a figure.</span><br></p><p dir="ltr">The perimeter of a trapezoid is the sum of the sides.</p><p dir="ltr">perimeter= {baseA} + {sideBD} + {baseB} + {sideAC}</p><p dir="ltr">perimeter = {perimeter}&nbsp;{unit}</p><p dir="ltr">The units are {unit} because distance is measured on a ruler.</p><br><p></p></div>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[xc={3:5:1};
ya={6:10:1};
xd={6:8:1};
xa={0:2:1};
yc={1:4:1};
xb={9:11:1};

#which side will be the base

unit={"ft","yards","inches","mm","meters","cm","km"};
colors=shuffle(["red","green","yellow","blue","purple","orange"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[yb=ya;
yd=yc;
baseA=xb-xa;
baseB=xd-xc;
height=ya-yc;
area=.5*height*(baseA+baseB);
midX=xc;
midY=.5*(yc+ya);
color1=colors[0];
color2=colors[1];
sideAC=round(sqrt(pow(xa-xc,2)+pow(ya-yc,2)),2);
sideBD=round(sqrt(pow(xb-xd,2)+pow(yb-yd,2)),2);
units=[unit,join("",unit,"<sup>2</sup>"),join("",unit,"<sup>3</sup>")];
perimeter=baseA+baseB+sideAC+sideBD;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[perimeter,0]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table>
    <tbody>
        <tr>
            <td>Perimeter= {_0}</td>
            <td> {_1:units}</td>
        </tr>
    </tbody>
</table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L59- Pie Charts</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360913  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-A-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=round(D1/sumNum*100,2);
P2=round(D2/sumNum*100,2);
P3=round(D3/sumNum*100,2);
P4=round(D4/sumNum*100,2);
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>0</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360914  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-B-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph> 
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
               <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=D1/sumNum*100;
P2=D2/sumNum*100;
P3=D3/sumNum*100;
P4=D4/sumNum*100;
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360915  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-C-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=round(D1/sumNum*100,2);
P2=round(D2/sumNum*100,2);
P3=round(D3/sumNum*100,2);
P4=round(D4/sumNum*100,2);
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>2</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360916  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-D-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=round(D1/sumNum*100,2);
P2=round(D2/sumNum*100,2);
P3=round(D3/sumNum*100,2);
P4=round(D4/sumNum*100,2);
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>3</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360909  -->
  <question type="formulas">
    <name>
      <text>L59- Section of pie chart</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Which pie graph has a {C1} slice showing {percent}% of the pie?

<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},100-{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,
                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
            <td> </td>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},100-{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},100-{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
            <td> </td>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},100-{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="300" height="300"> var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-5,15,15,-5],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{percent},100-{percent}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','white'],
    labels:['{percent}%',' '],
    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,
    highlightColors:['{C1}','yellow'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[25,10,50,15],[90,10,100,30],[65,10,75,15],[10,30,60,90],[33,66,87,17],[40,60,50,10],[100,20,60,90],[10,2,40,80],[60,90,10,30]};
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);
order=shuffle([0,1,2,3]); #for answers
quesOrder=shuffle([0,1,2,3]); # for the question]]></text>
</varsrandom>
<varsglobal><text><![CDATA[Data=[Data[quesOrder[0]],Data[quesOrder[1]],Data[quesOrder[2]],Data[quesOrder[3]]];
C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
percent=Data[0];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>order[_0]==0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360910  -->
  <question type="formulas">
    <name>
      <text>L59- Section of pie chart by data</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[{numberC} people were surveyed to determine their favorite color.&nbsp; {numChoice} people chose {C1}.&nbsp; Which chart shows the correct size slice showing the data for the number of people who chose {C1}?

<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},100-{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,
                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
            <td> </td>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},100-{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},100-{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
            <td> </td>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},100-{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[{numChoice} out of {number} people chose {C1}<br>&nbsp;\(\frac{{numChoice}}{{total}}\) = \(\frac{Percent}{100}\)<br>
(\(\frac{{numChoice}}{{total}}\))( \(\frac{{factor}}{{factor}}\)) = \(\frac{{percent}}{100}\)<br>The section must be {percent}% of the pie


<jsxgraph width="300" height="300"> var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-5,15,15,-5],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{percent},100-{percent}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','white'],
    labels:['{percent}%',' '],
    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:2,
    highlightColors:['{C1}','yellow'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[25,10,50,15],[90,10,100,30],[65,10,75,15],[10,30,60,90],[30,65,85,10],[40,60,50,10],[100,20,60,90],[10,5,40,80],[60,90,10,30]};
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);
order=shuffle([0,1,2,3]); #for answers
quesOrder=shuffle([0,1,2,3]); # for the question]]></text>
</varsrandom>
<varsglobal><text><![CDATA[Data=[Data[quesOrder[0]],Data[quesOrder[1]],Data[quesOrder[2]],Data[quesOrder[3]]];
C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
percent=Data[0];
#must change for each question
factor=5;
numChoice=percent/factor;

numberC="Twenty";
number="twenty";
total=20;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>order[_0]==0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360911  -->
  <question type="formulas">
    <name>
      <text>L59- Section of pie chart by data (many factors)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[{total} people were surveyed to determine their favorite color.&nbsp; {numChoice} people chose {C1}.&nbsp; Which chart shows the correct size slice showing the data for the number of people who chose {C1}?

<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},100-{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
            <td> </td>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},100-{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},100-{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
            <td> </td>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},100-{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','white'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,

                    highlightColors:['{C1}','yellow'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[{numChoice} out of {total} people chose {C1}<br>&nbsp;\(\frac{{numChoice}}{{total}}\) = \(\frac{Percent}{100}\)<br>
To change the fraction such that the denominator equals 100, multiply the numerator and denominator by {factor}.  

(\(\frac{{numChoice}}{{total}}\))( \(\frac{{factor}}{{factor}}\)) = \(\frac{{percent}}{100}\)<br>The section must be {percent}% of the pie


<jsxgraph width="300" height="300"> var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-5,15,15,-5],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{percent},100-{percent}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','white'],
    labels:['{percent}%',' '],
    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
    highlightColors:['{C1}','yellow'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[25,10,50,15],[90,10,100,30],[65,10,75,15],[10,30,60,90],[30,65,85,10],[40,60,50,10],[100,20,60,90],[10,25,40,80],[60,90,10,30]};
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);
order=shuffle([0,1,2,3]); #for answers
quesOrder=shuffle([0,1,2,3]); # for the question
randFactor={0,1,2,3};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[Data=[Data[quesOrder[0]],Data[quesOrder[1]],Data[quesOrder[2]],Data[quesOrder[3]]];
C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
percent=Data[0];
#must change for each question
factors=[1,2,5,10];
factor=factors[randFactor];
numChoice=percent/factor;
total=100/factor;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>order[_0]==0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>percent</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What percent of the pie is shaded? {_0}%</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">\(\frac{{numChoice}}{{total}}\) = \(\frac{{percent}}{{100}}\)</p><p dir="ltr" style="text-align: left;">Therefore {percent}% is shaded.</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360912  -->
  <question type="formulas">
    <name>
      <text>L59--Percent-Fraction-Decimals</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p></p>Fill in the percent, fraction, and decimal equivalence chart.<br>
<table width="75%">
    <tbody>
        <tr style="border-bottom:2px solid black">
            <td width="30%" style="text-align: center; border-right:1px solid black;"><strong>Percent</strong></td>
            <td width="1.5%" style="text-align: center;">&nbsp; &nbsp;&nbsp;</td>
            <td width="30%" style="text-align: center; border-right:1px solid black;"><strong>Fraction</strong></td>
            <td width="1.5%" style="text-align: center;">&nbsp; &nbsp;&nbsp;</td>
            <td width="30%" style="text-align: center;"><strong>Decimal</strong></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: center; border-right:1px solid black;">{#A}</td><td></td><td style="border-right:1px solid black;"><br><table width="100%"><tbody><tr><td style="text-align: center; border-bottom: 1px solid black;">{f1Num}</td></tr><tr><td style="text-align: center;">{f1Den}</td></tr></tbody></table><br></td><td></td>
            <td style="text-align: center;">{#B}</td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: left;  border-right:1px solid black;">{p2}%</td><td></td><td style="text-align: center; border-right:1px solid black;">{#C}</td>
            <td></td>
            <td style="text-align: center; border-right:1px solid black;">{#D}</td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: center; border-right:1px solid black;">{#E}</td><td style="text-align: center;"></td><td style="text-align: center; border-right:1px solid black;"><span style="font-size: 0.9375rem;">{#F}</span></td>
            <td></td>
            <td style="text-align: center;">{d3}</td>
        </tr>
        
    </tbody>
</table><br>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>6.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>random=shuffle([1,2,3,4,5,6,7,8,9,10,11,12]);</text>
</varsrandom>
<varsglobal><text>percent=[100,75,50,25,10,20,30,40,50,60,70,80,90];
fractionNum=[1,3,1,1,1,1,3,2,1,3,7,4,9];
#fractions=[[1,1],[3,4],[1,2],[1,4],[1,10],[1,5],[3,10],[2,5],[1,2],[3,5],[7,10],[4,5],[9,10]];
fractionDen=[1,4,2,4,10,5,10,5,2,5,10,5,10];
decimal=[1,.75,.5,.25,.1,.2,.3,.4,.5,.6,.7,.8,.9];
p1=percent[random[0]];
f1Num=fractionNum[random[0]];
f1Den=fractionDen[random[0]];
d1=decimal[random[0]];
p2=percent[random[1]];
f2Num=fractionNum[random[1]];
f2Den=fractionDen[random[1]];
d2=decimal[random[1]];
p3=percent[random[2]];
f3Num=fractionNum[random[2]];
f3Den=fractionDen[random[2]];
d3=decimal[random[2]];

</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#A</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>p1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{_0}%</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Percent means out of 100.&nbsp;&nbsp;<br>Rewrite the fraction with a denominator of 100.<br>(\(\frac{{f1Num}}{{f1Den}}\))(\(\frac{{=100/f1Den}}{{=100/f1Den}}\)) = \(\frac{{p1}}{100}\)
  <br><strong>{p1}%</strong></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text>#B</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>d1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[Use the percent value to find the decimal value.<br>To change a percent to a decimal divide by 100.<br>{p1}&nbsp;÷ 100 = <strong>{d1}</strong><br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>2</text>
 </partindex>
 <placeholder>
  <text>#C</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text>GCF=gcd(p2,100);
p2Num=p2/GCF;
p2Den=100/GCF;</text>
 </vars1>
 <answer>
  <text>[f2Num,f2Den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[((_0/_1) ==(f2Num/f2Den)) && (gcd(_0,_1) == 1)]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table><tbody><tr><td style="border-bottom: 1px solid black;">{_0}</td></tr><tr><td>{_1}</td></tr></tbody></table>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">To change the percent to a fraction write the value of the percent over 100.</p><p dir="ltr" style="text-align: left;">{p2}% = \(\frac{<span style="font-size: 0.9375rem;">{p2}}{{100}}\)&nbsp; &nbsp;Reduce the fraction</span></p><p dir="ltr" style="text-align: left;">{p2}&nbsp;÷ {GCF} = {p2Num}</p><p dir="ltr" style="text-align: left;">100&nbsp;÷ {GCF} = {p2Den}</p><p dir="ltr" style="text-align: left;">The reduced fraction is:&nbsp; \(\frac{{p2Num}}{{p2Den}}\)</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>3</text>
 </partindex>
 <placeholder>
  <text>#D</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>d2</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Use the percent value to find the decimal value.<br>To change a percent to a decimal divide by 100.<br>{p2}&nbsp;÷ 100 =&nbsp;<strong>{d2}</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>4</text>
 </partindex>
 <placeholder>
  <text>#E</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>p3</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{_0}%</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Use the decimal value to find the percent value.<br>To change a decimal to a percent multiply by 100.<br>({d1})(100) =&nbsp;<strong>{p1}%</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>5</text>
 </partindex>
 <placeholder>
  <text>#F</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text>GCF=gcd(p3,100);
p3Num=p3/GCF;
p3Den=100/GCF;</text>
 </vars1>
 <answer>
  <text>[f3Num,f3Den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[((_0/_1) ==(f3Num/f3Den)) && (gcd(_0,_1) == 1)]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><table><tbody><tr><td>{_0}</td></tr><tr><td>{_1}</td></tr></tbody></table><br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">To change the percent to a fraction write the value of the percent over 100.</p><p dir="ltr">{p3}% = \(\frac{{p3}}{{100}}\)&nbsp; &nbsp;Reduce the fraction</p><p dir="ltr">{p3}&nbsp;÷ {GCF} = {p3Num}</p><p dir="ltr">100&nbsp;÷ {GCF} = {p3Den}</p><p dir="ltr">The reduced fraction is:&nbsp; \(\frac{{p3Num}}{{p3Den}}\)</p><br><p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360917  -->
  <question type="formulas">
    <name>
      <text>L59--Percent-Fraction-Decimals</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p></p>Fill in the percent, fraction, and decimal equivalence chart.<br>
<table width="75%">
    <tbody>
        <tr style="border-bottom:2px solid black">
            <td width="30%" style="text-align: center; border-right:1px solid black;"><strong>Percent</strong></td>
            <td width="1.5%" style="text-align: center;">&nbsp; &nbsp;&nbsp;</td>
            <td width="30%" style="text-align: center; border-right:1px solid black;"><strong>Fraction</strong></td>
            <td width="1.5%" style="text-align: center;">&nbsp; &nbsp;&nbsp;</td>
            <td width="30%" style="text-align: center;"><strong>Decimal</strong></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: center; border-right:1px solid black;">{#A}</td><td></td><td style="border-right:1px solid black;"><br><table width="100%"><tbody><tr><td style="text-align: center; border-bottom: 1px solid black;">{f1Num}</td></tr><tr><td style="text-align: center;">{f1Den}</td></tr></tbody></table><br></td><td></td>
            <td style="text-align: center;">{#B}</td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: left;  border-right:1px solid black;">{p2}%</td><td></td><td style="text-align: center; border-right:1px solid black;">{#C}</td>
            <td></td>
            <td style="text-align: center; border-right:1px solid black;">{#D}</td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: center; border-right:1px solid black;">{#E}</td><td style="text-align: center;"></td><td style="text-align: center; border-right:1px solid black;"><span style="font-size: 0.9375rem;">{#F}</span></td>
            <td></td>
            <td style="text-align: center;">{d3}</td>
        </tr>
        
    </tbody>
</table><br>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>6.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>random=shuffle([1,2,3,4,5,6,7,8,9,10,11,12]);</text>
</varsrandom>
<varsglobal><text>percent=[100,75,50,25,10,20,30,40,50,60,70,80,90];
fractionNum=[1,3,1,1,1,1,3,2,1,3,7,4,9];
#fractions=[[1,1],[3,4],[1,2],[1,4],[1,10],[1,5],[3,10],[2,5],[1,2],[3,5],[7,10],[4,5],[9,10]];
fractionDen=[1,4,2,4,10,5,10,5,2,5,10,5,10];
decimal=[1,.75,.5,.25,.1,.2,.3,.4,.5,.6,.7,.8,.9];
p1=percent[random[0]];
f1Num=fractionNum[random[0]];
f1Den=fractionDen[random[0]];
d1=decimal[random[0]];
p2=percent[random[1]];
f2Num=fractionNum[random[1]];
f2Den=fractionDen[random[1]];
d2=decimal[random[1]];
p3=percent[random[2]];
f3Num=fractionNum[random[2]];
f3Den=fractionDen[random[2]];
d3=decimal[random[2]];

</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#A</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>p1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{_0}%</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Percent means out of 100.&nbsp;&nbsp;<br>Rewrite the fraction with a denominator of 100.<br>(\(\frac{{f1Num}}{{f1Den}}\))(\(\frac{{=100/f1Den}}{{=100/f1Den}}\)) = \(\frac{{p1}}{100}\)
  <br><strong>{p1}%</strong></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text>#B</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>d1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[Use the percent value to find the decimal value.<br>To change a percent to a decimal divide by 100.<br>{p1}&nbsp;÷ 100 = <strong>{d1}</strong><br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>2</text>
 </partindex>
 <placeholder>
  <text>#C</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text>GCF=gcd(p2,100);
p2Num=p2/GCF;
p2Den=100/GCF;</text>
 </vars1>
 <answer>
  <text>[f2Num,f2Den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[((_0/_1) ==(f2Num/f2Den)) && (gcd(_0,_1) == 1)]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table><tbody><tr><td style="border-bottom: 1px solid black;">{_0}</td></tr><tr><td>{_1}</td></tr></tbody></table>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">To change the percent to a fraction write the value of the percent over 100.</p><p dir="ltr" style="text-align: left;">{p2}% = \(\frac{<span style="font-size: 0.9375rem;">{p2}}{{100}}\)&nbsp; &nbsp;Reduce the fraction</span></p><p dir="ltr" style="text-align: left;">{p2}&nbsp;÷ {GCF} = {p2Num}</p><p dir="ltr" style="text-align: left;">100&nbsp;÷ {GCF} = {p2Den}</p><p dir="ltr" style="text-align: left;">The reduced fraction is:&nbsp; \(\frac{{p2Num}}{{p2Den}}\)</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>3</text>
 </partindex>
 <placeholder>
  <text>#D</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>d2</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Use the percent value to find the decimal value.<br>To change a percent to a decimal divide by 100.<br>{p2}&nbsp;÷ 100 =&nbsp;<strong>{d2}</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>4</text>
 </partindex>
 <placeholder>
  <text>#E</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>p3</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{_0}%</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Use the decimal value to find the percent value.<br>To change a decimal to a percent multiply by 100.<br>({d1})(100) =&nbsp;<strong>{p1}%</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>5</text>
 </partindex>
 <placeholder>
  <text>#F</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text>GCF=gcd(p3,100);
p3Num=p3/GCF;
p3Den=100/GCF;</text>
 </vars1>
 <answer>
  <text>[f3Num,f3Den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[((_0/_1) ==(f3Num/f3Den)) && (gcd(_0,_1) == 1)]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><table><tbody><tr><td>{_0}</td></tr><tr><td>{_1}</td></tr></tbody></table><br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">To change the percent to a fraction write the value of the percent over 100.</p><p dir="ltr">{p3}% = \(\frac{{p3}}{{100}}\)&nbsp; &nbsp;Reduce the fraction</p><p dir="ltr">{p3}&nbsp;÷ {GCF} = {p3Num}</p><p dir="ltr">100&nbsp;÷ {GCF} = {p3Den}</p><p dir="ltr">The reduced fraction is:&nbsp; \(\frac{{p3Num}}{{p3Den}}\)</p><br><p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360923  -->
  <question type="formulas">
    <name>
      <text>L59--Percent-Fraction-Decimals</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p></p>Fill in the percent, fraction, and decimal equivalence chart.<br>
<table width="75%">
    <tbody>
        <tr style="border-bottom:2px solid black">
            <td width="30%" style="text-align: center; border-right:1px solid black;"><strong>Percent</strong></td>
            <td width="1.5%" style="text-align: center;">&nbsp; &nbsp;&nbsp;</td>
            <td width="30%" style="text-align: center; border-right:1px solid black;"><strong>Fraction</strong></td>
            <td width="1.5%" style="text-align: center;">&nbsp; &nbsp;&nbsp;</td>
            <td width="30%" style="text-align: center;"><strong>Decimal</strong></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: center; border-right:1px solid black;">{#A}</td><td></td><td style="border-right:1px solid black;"><br><table width="100%"><tbody><tr><td style="text-align: center; border-bottom: 1px solid black;">{f1Num}</td></tr><tr><td style="text-align: center;">{f1Den}</td></tr></tbody></table><br></td><td></td>
            <td style="text-align: center;">{#B}</td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: left;  border-right:1px solid black;">{p2}%</td><td></td><td style="text-align: center; border-right:1px solid black;">{#C}</td>
            <td></td>
            <td style="text-align: center; border-right:1px solid black;">{#D}</td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td style="text-align: center; border-right:1px solid black;">{#E}</td><td style="text-align: center;"></td><td style="text-align: center; border-right:1px solid black;"><span style="font-size: 0.9375rem;">{#F}</span></td>
            <td></td>
            <td style="text-align: center;">{d3}</td>
        </tr>
        
    </tbody>
</table><br>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>6.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>random=shuffle([1,2,3,4,5,6,7,8,9,10,11,12]);</text>
</varsrandom>
<varsglobal><text>percent=[100,75,50,25,10,20,30,40,50,60,70,80,90];
fractionNum=[1,3,1,1,1,1,3,2,1,3,7,4,9];
#fractions=[[1,1],[3,4],[1,2],[1,4],[1,10],[1,5],[3,10],[2,5],[1,2],[3,5],[7,10],[4,5],[9,10]];
fractionDen=[1,4,2,4,10,5,10,5,2,5,10,5,10];
decimal=[1,.75,.5,.25,.1,.2,.3,.4,.5,.6,.7,.8,.9];
p1=percent[random[0]];
f1Num=fractionNum[random[0]];
f1Den=fractionDen[random[0]];
d1=decimal[random[0]];
p2=percent[random[1]];
f2Num=fractionNum[random[1]];
f2Den=fractionDen[random[1]];
d2=decimal[random[1]];
p3=percent[random[2]];
f3Num=fractionNum[random[2]];
f3Den=fractionDen[random[2]];
d3=decimal[random[2]];

</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#A</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>p1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{_0}%</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Percent means out of 100.&nbsp;&nbsp;<br>Rewrite the fraction with a denominator of 100.<br>(\(\frac{{f1Num}}{{f1Den}}\))(\(\frac{{=100/f1Den}}{{=100/f1Den}}\)) = \(\frac{{p1}}{100}\)
  <br><strong>{p1}%</strong></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text>#B</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>d1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[Use the percent value to find the decimal value.<br>To change a percent to a decimal divide by 100.<br>{p1}&nbsp;÷ 100 = <strong>{d1}</strong><br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>2</text>
 </partindex>
 <placeholder>
  <text>#C</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text>GCF=gcd(p2,100);
p2Num=p2/GCF;
p2Den=100/GCF;</text>
 </vars1>
 <answer>
  <text>[f2Num,f2Den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[((_0/_1) ==(f2Num/f2Den)) && (gcd(_0,_1) == 1)]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table><tbody><tr><td style="border-bottom: 1px solid black;">{_0}</td></tr><tr><td>{_1}</td></tr></tbody></table>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">To change the percent to a fraction write the value of the percent over 100.</p><p dir="ltr" style="text-align: left;">{p2}% = \(\frac{<span style="font-size: 0.9375rem;">{p2}}{{100}}\)&nbsp; &nbsp;Reduce the fraction</span></p><p dir="ltr" style="text-align: left;">{p2}&nbsp;÷ {GCF} = {p2Num}</p><p dir="ltr" style="text-align: left;">100&nbsp;÷ {GCF} = {p2Den}</p><p dir="ltr" style="text-align: left;">The reduced fraction is:&nbsp; \(\frac{{p2Num}}{{p2Den}}\)</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>3</text>
 </partindex>
 <placeholder>
  <text>#D</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>d2</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Use the percent value to find the decimal value.<br>To change a percent to a decimal divide by 100.<br>{p2}&nbsp;÷ 100 =&nbsp;<strong>{d2}</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>4</text>
 </partindex>
 <placeholder>
  <text>#E</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>p1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{_0}%</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Use the decimal value to find the percent value.<br>To change a decimal to a percent multiply by 100.<br>({d1})(100) =&nbsp;<strong>{p1}%</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>5</text>
 </partindex>
 <placeholder>
  <text>#F</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text>GCF=gcd(p3,100);
p3Num=p3/GCF;
p3Den=100/GCF;</text>
 </vars1>
 <answer>
  <text>[f3Num,f3Den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[((_0/_1) ==(f3Num/f3Den)) && (gcd(_0,_1) == 1)]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><table><tbody><tr><td>{_0}</td></tr><tr><td>{_1}</td></tr></tbody></table><br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">To change the percent to a fraction write the value of the percent over 100.</p><p dir="ltr">{p3}% = \(\frac{{p3}}{{100}}\)&nbsp; &nbsp;Reduce the fraction</p><p dir="ltr">{p3}&nbsp;÷ {GCF} = {p3Num}</p><p dir="ltr">100&nbsp;÷ {GCF} = {p3Den}</p><p dir="ltr">The reduced fraction is:&nbsp; \(\frac{{p3Num}}{{p3Den}}\)</p><br><p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L59- Pie Charts/L59- Multiple Choice Pie Chart</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360944  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-A-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=round(D1/sumNum*100,2);
P2=round(D2/sumNum*100,2);
P3=round(D3/sumNum*100,2);
P4=round(D4/sumNum*100,2);
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>0</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360945  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-B-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph> 
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
               <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=D1/sumNum*100;
P2=D2/sumNum*100;
P3=D3/sumNum*100;
P4=D4/sumNum*100;
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>1</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360946  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-C-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=round(D1/sumNum*100,2);
P2=round(D2/sumNum*100,2);
P3=round(D3/sumNum*100,2);
P4=round(D4/sumNum*100,2);
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>2</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360947  -->
  <question type="formulas">
    <name>
      <text>L59- Make a pie chart-D-answer Mult Choice</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The students in art class were asked what their favorite color is. The data is: <table>
    <tbody>
        <tr>
            <td style="text-align: center;"><strong>&nbsp;Color&nbsp;</strong></td>
            <td><strong>Number of Students</strong></td>
        </tr>
        <tr>
            <td style="text-align: center;">{C1}</td>
            <td style="text-align: center;">{D1}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C2}</td>
            <td style="text-align: center;">{D2}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C3}</td>
            <td style="text-align: center;">{D3}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{C4}</td>
            <td style="text-align: center;">{D4}</td>
        </tr>
    </tbody>
</table>

Which pie chart correctly displays the data?<table>
    <tbody>
        <tr>
            <td>A.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D4},{D3},{D2},{D1}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P4}%','{C2} {P3}%', '{C3} {P2}%','{C4} {P1}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>B.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D2},{D1},{D4},{D3}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P2}%','{C2} {P1}%', '{C3} {P4}%','{C4} {P3}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>C.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-2.4,8,13.6,-4],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D3},{D4},{D1},{D2}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P3}%','{C2} {P4}%', '{C3} {P1}%','{C4} {P2}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
        <tr>
            <td>D.</td>
            <td>
                <jsxgraph width="150" height="150"> var board=JXG.JSXGraph.initBoard(BOARDID,{
                    boundingbox:[-5,15,15,-5],
                    axis:false,
                    grid:false,
                    showCopyright:false,
                    showNavigation:false,
                    keepaspectratio:true
                    });

                    var dataArr = [{D1},{D2},{D3},{D4}];

                    board.containerObj.style.backgroundColor = 'white';
                    board.options.label.strokeColor = 'black';

                    board.suspendUpdate();

                    var a = board.create('chart', dataArr,
                    {chartStyle:'pie',
                    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
                    fillOpacity:0.8, center:[5,5], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:1,
                    labels:['{C1} {P1}%','{C2} {P2}%', '{C3} {P3}%','{C4} {P4}%'],
                    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
                    highlightOnSector:true,
                    highlightBySize:true,
                    gradient:'linear'
                    }
                    );
                    board.unsuspendUpdate();
                </jsxgraph>
            </td>
        </tr>
    </tbody>
</table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="300">&nbsp;var board=JXG.JSXGraph.initBoard(BOARDID,{
    boundingbox:[-2.4,8,13.6,-4],
    axis:false,
    grid:false,
    showCopyright:false,
    showNavigation:false,
    keepaspectratio:true
    });

    var dataArr = [{D1},{D2},{D3},{D4}];

    board.containerObj.style.backgroundColor = 'white';
    board.options.label.strokeColor = 'black';

    board.suspendUpdate();

    var a = board.create('chart', dataArr,
    {chartStyle:'pie',
    colors:['{C1}','{C2}','{C3}','{C4}','#87CCEE','#0092CE'],
    fillOpacity:0.8, center:[5,2], strokeColor:'black', highlightStrokeColor:'black', strokeWidth:4,
    labels:['{C1}-{P1}%','{C2}-{P2}%', '{C3}-{P3}%','{C4}-{P4}%'],
    highlightColors:['{C1}','{C2}','{C3}','{C4}'],
    highlightOnSector:true,
    highlightBySize:true,
    gradient:'linear'
    }
    );
    board.unsuspendUpdate();
</jsxgraph>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[Data={[30,20,50,0],[5,15,50,30],[65,8,12,15],[40,30,20,10],[30,35,15,20],[40,30,10,20],[20,15,25,40],[1,5,4,10],[6,4,8,3]};
order=shuffle([0,1,2,3]);
randColors=shuffle(["red","green","blue","orange","yellow","pink","purple","brown","black","magenta"]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[C1=randColors[0];
C2=randColors[1];
C3=randColors[2];
C4=randColors[3];
D1=Data[order[0]];
D2=Data[order[1]];
D3=Data[order[2]];
D4=Data[order[3]];
choices=["A","B","C","D"];
sumNum=D1+D2+D3+D4;
P1=round(D1/sumNum*100,2);
P2=round(D2/sumNum*100,2);
P3=round(D3/sumNum*100,2);
P4=round(D4/sumNum*100,2);
maxA=-1;
maxA=(D1>maxA)?0:maxA;
maxA=(D2>maxA)?1:maxA;
maxA=(D3>maxA)?2:maxA;
maxA=(D4>maxA)?3:maxA;
dData=fill(4,0);
dData=pick(maxA,[D1,D3,D4,D2],[D3,D2,D4,D1],[D4,D1,D3,D2],[D3,D1,D2,D4]);
dD1=dData[0];
dD2=dData[1];
dD3=dData[2];
dD4=dData[3];
dP1=dD1/sumNum*100;
dP2=dD2/sumNum*100;
dP3=dD3/sumNum*100;
dP4=dD4/sumNum*100;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>3</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">What chart correctly shows the data? {_0:choices:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L60- Equations with Mixed Numbers</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360950  -->
  <question type="formulas">
    <name>
      <text>TL60 - Addition Equation Mixed Numbers</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Solve for {var}:</h3>
<h3 style="text-align: left;">{var} + {whole1}\(\frac{{aNum}}{{aDen}}\) = {whole2}\(\frac{{bNum}}{{bDen}}\)</h3>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><table>
    <tbody>
        <tr>
            <td>
                <p>{var} + {whole1}\(\frac{{aNum}}{{aDen}}\) = {whole2}\(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td><p>&nbsp; &nbsp; &nbsp; &nbsp;</p></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp; <span class="" style="color: rgb(255, 51, 102);">- {whole1}\(\frac{{aNum}}{{aDen}}\)&nbsp; &nbsp; -{whole1}\(\frac{{aNum}}{{aDen}}\)</span></p>

            </td>
            <td><p><br></p></td>
            <td>
                <p>subtract <span class="" style="color: rgb(255, 51, 102);">{whole1}\(\frac{{aNum}}{{aDen}}\)<br></span> on both sides</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp;{var}&nbsp; &nbsp; &nbsp; &nbsp;= <span class="" style="color: rgb(51, 102, 255);">&nbsp;{ansW}\(\frac{{redN}}{{redD}}\)&nbsp;</span></p>

            </td>
            <td></td>
            <td>
                <p>simplify</p>
            </td>
        </tr>
        <tr>
            <td colspan="3">
                <div class="editor-indent" style="margin-left: 30px;">
                    <div class="editor-indent" style="margin-left: 30px;">
                        <p style="text-align: left;"><strong>Check</strong></p>
                    </div>
                </div>
            </td>
        </tr>
        <tr>
            <td>

                <p>{var} + {whole1}\(\frac{{aNum}}{{aDen}}\) = {whole2}\(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>{ansW}\(\frac{{redN}}{{redD}}\)&nbsp; + {whole1}\(\frac{{aNum}}{{aDen}}\) ?= {whole2}\(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>Substitute {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>You can use ?= to show you are testing if the answer is correct.</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>{ansW}\(\frac{{bNum}}{{bDen}}\) ?= {ansW}\(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>It is true, therefore {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp; is the correct answer.</p>
            </td>
        </tr>
    </tbody>
</table>

<p dir="ltr" style="text-align: left;"></p>
<p dir="ltr"></p>
<h5><strong><span class="" style="color: rgb(255, 51, 102);">Directions for Subtracting the Fractions:</span></strong></h5><h5>1.&nbsp; The least common multiple of {number1} and {number2} is&nbsp;<strong>{least}</strong></h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">The multiples of {number1} are: {multiples1}</p>
    <p dir="ltr">The multiples of {number2} are: {multiples2}</p>
</div>
<h5>2.&nbsp; &nbsp;Use the&nbsp;identity property of multiplication: A number multiplied by one equals the number.&nbsp; (7 • 1 = 7)</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <table>
        <tbody>
            <tr>
                <td>
                    <p>\(\frac{{factor0}}{{factor0}}\) = 1</p>
                    <p>\( \frac{{num0}}{{den0}} \)&nbsp;•&nbsp;\(\frac{{factor0}}{{factor0}}\)&nbsp;=&nbsp;\( \frac{{ansNum0}}{{ansDen0}} \)</p>
                </td>
                <td>&nbsp; &nbsp; &nbsp;</td>
                <td>
                    <p>\(\frac{{factor1}}{{factor1}}\) = 1</p>
                    <p>\( \frac{{num1}}{{den1}} \)&nbsp;•&nbsp;\(\frac{{factor1}}{{factor1}}\)&nbsp;=&nbsp;\( \frac{{ansNum1}}{{ansDen1}} \)</p>
                </td>
            </tr>
        </tbody>
    </table>
    <p></p>
</div>
<h5>3.&nbsp; Calculate the {answer}.</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">{opWord} the numerators:&nbsp; {ansNum0}{opSign}{ansNum1} = {impN}&nbsp;</p>
    <p dir="ltr">Keep the denominator:&nbsp; {least}</p>
    <p dir="ltr">The sum of the fractions is \(\frac{{impN}}{{least}}\)</p>
</div>
<p dir="ltr"></p>
<h5>4.&nbsp; Write the answer in simplest form.</h5>
<div><br>

</div>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr"><span style="font-size: 0.9375rem;">{FB1}</span></p>
    <p dir="ltr">The fractional part is \(\frac{{ansN}}{{ansD}}\)</p>
    <p dir="ltr">Determine the GCF of the numerator and denominator:</p>
    <p dir="ltr">The factors of {ansN}: {=FB[ansN]}</p>
    <p dir="ltr">The factors of {ansD}: {=FB[ansD]}</p>
    <p dir="ltr">The GCF (greatest common factor) of {ansN} and {ansD} is {gcfND}.</p>
    <table>
        <tbody>
            <tr>
                <td style="border-bottom: 1px solid black">{ansN}</td>
                <td rowspan="2">÷<br></td>
                <td style="border-bottom: 1px solid black">{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{ansN}÷{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{=ansN/gcfND}</td>
            </tr>
            <tr>
                <td>{ansD}</td>
                <td>{gcfND}</td>
                <td>{ansD}÷{gcfND}</td>
                <td>{=ansD/gcfND}</td>
            </tr>
        </tbody>
    </table>
</div>





<br>{ansW}\(\frac{{ansN}}{{ansD}}\) =&nbsp; {ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>
<p></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[var={"x","p","t","c","y","z"};
whole1={1:4:1};
whole2={5:9:1};
Tfraction0={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
Tfraction1={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[temp=whole1;

fractionNums=pick(Tfraction0[0]/Tfraction0[1]>Tfraction1[0]/Tfraction1[1],[Tfraction0[0],Tfraction0[1],Tfraction1[0],Tfraction1[1]],[Tfraction1[0],Tfraction1[1],Tfraction0[0],Tfraction0[1]]);

aNum=fractionNums[0];
aDen=fractionNums[1];
bNum=fractionNums[2];
bDen=fractionNums[3];
y={-100:100:1};
z={-100:100:1};
t={-100:100:1};
p={-100:100:1};
c={-100:100:1};
randOp=0;
opSign=pick(randOp," - "," + ");
opWord=pick(randOp,"Subtract","Add");
frac0=Tfraction0[0]/Tfraction0[1];
frac1=Tfraction1[0]/Tfraction1[1];
fraction0=pick(frac0 >frac1,Tfraction1,Tfraction0);
fraction1=pick(frac0 >frac1,Tfraction0,Tfraction1);
numbers=[fraction0[1],fraction1[1]];
number1=numbers[0];
number2=numbers[1];
operation=pick(randOp,"-","+");
answer=pick(randOp,"difference","sum");
least=lcm(number1,number2);

multiples1=pick(number1==least,join("",number1),join("","<b>",number1,"</b>"));
multiples2=pick(number2==least,join("",number2),join("","<b>",number2,"</b>"));
for(i:[2:11]){
multiples1=pick(number1*i == least,join("",multiples1,", ",number1*i),join("",multiples1,", <b>",number1*i,"</b>"));

multiples2=pick(number2*i == least,join("",multiples2,", ",number2*i),join("",multiples2,", <b>",number2*i,"</b>"));
}

num0=fraction0[0];
den0=fraction0[1];
ansNum0=num0*(least/den0);
ansDen0=least;
factor0=least/den0;

num1=fraction1[0];
den1=fraction1[1];
ansNum1=num1*(least/den1);
ansDen1=least;
factor1=least/den1;

ansN=pick(randOp,ansNum0-ansNum1,ansNum0+ansNum1);
impN=ansN;
ansD=least;
ansW=floor(ansN/ansD);
ansN=ansN-(ansW*ansD);

FB1=pick(impN>ansN,join("","The numerator is less than the denominator.  The whole number is ",whole2-whole1," (because ",whole2," - ",whole1," is ",whole2-whole1,")."),join("","The numerator is larger than the denominator.<br> Determine how many times the denominator can divide into the numerator.<br>",impN,"/",least," = ",ansW," with ",ansN," left over. <br>Put the left over amount in the numerator and keep the same denominator.<br> The whole number is ",ansW+whole2-whole1," (because the whole numbers need to be added included: ",whole2," - ",whole1," is ",whole2-whole1,")."));
ansW=ansW+(whole2-whole1);
gcfND=gcd(ansN,ansD);
redN=ansN/gcfND;
redD=ansD/gcfND;
FB=["0","1","1 2","1 3","1 2 4","1 5","1 2 3 6","1 7","1 2 4 8","1 3 9","1 2 5 10","1 11","1 2 3 4 6 12","1 13","1 2 7 14","1 3 5 15","1 2 4 8 16","1 17","1 2 3 6 9 18","1 19","1 2 4 5 10 20","1 3 7 21","1 2 11 22","1 23","1 2 3 4 6 8 12 24","1 5 25","1 2 13 26","1 3 9 27","1 2 4 7 14 28","1 29","1 2 3 5 6 10 15 30","1 31","1 2 4 8 16 32","1 3 11 33","1 2 17 34","1 5 7 35","1 2 3 4 6 9 12 18 36","1 37","1 2 19 38","1 3 13 39","1 2 4 5 8 10 20 40","1 41","1 2 3 6 7 14 21 42","1 43","1 2 4 11 22 44","1 3 5 9 15 45","1 2 23 46","1 47","1 2 3 4 6 8 12 16 24 48","1 7 49","1 2 5 10 25 50","1 3 17 51","1 2 4 13 26 52","1 53","1 2 3 6 9 18 27 54","1 5 11 55","1 2 4 7 8 14 28 56","1 3 19 57","1 2 29 58","1 59","1 2 3 4 5 6 10 12 15 20 30 60","1 61","1 2 31 62","1 3 7 9 21 63","1 2 4 8 16 32 64","1 5 13 65","1 2 3 6 11 22 33 66","1 67","1 2 4 17 34 68","1 3 23 69","1 2 5 7 10 14 35 70","1 71","1 2 3 4 6 8 9 12 18 24 36 72","1 73","1 2 37 74","1 3 5 15 25 75","1 2 4 19 38 76","1 7 11 77","1 2 3 6 13 26 39 78","1 79","1 2 4 5 8 10 16 20 40 80","1 3 9 27 81","1 2 41 82","1 83","1 2 3 4 6 7 12 14 21 28 42 84","1 5 17 85","1 2 43 86","1 3 29 87","1 2 4 8 11 22 44 88","1 89","1 2 3 5 6 9 10 15 18 30 45 90","1 7 13 91","1 2 4 23 46 92","1 3 31 93","1 2 47 94","1 5 19 95","1 2 3 4 6 8 12 16 24 32 48 96","1 97","1 2 7 14 49 98","1 3 9 11 33 99","1 2 4 5 10 20 25 50 100"];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>3</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[ansW,redN,redD]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>((_0==ansW)*.4)+((redN/redD ==_1/_2)*.3)+(((gcd(redN,redD)) ==1)*.3)</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table>
    <tbody>
        <tr>
            <td rowspan="2">{var}=</td>
            <td rowspan="2">{_0}</td>
            <td style="border-bottom:1px solid black">{_1}</td>
        </tr>
        <tr>
            <td>{_2}</td>
        </tr>
    </tbody>
</table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360951  -->
  <question type="formulas">
    <name>
      <text>TL60 - Addition Equation with Fraction</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Solve for {var}:</h3>
<h3 style="text-align: left;">{var} + \(\frac{{aNum}}{{aDen}}\) = \(\frac{{bNum}}{{bDen}}\)</h3>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><table>
    <tbody>
        <tr>
            <td>
                <p>{var} +
                    \(\frac{{aNum}}{{aDen}}\) = \(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td><p>&nbsp; &nbsp; &nbsp; &nbsp;</p></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp; <span class="" style="color: rgb(255, 51, 102);">- \(\frac{{aNum}}{{aDen}}\)&nbsp; &nbsp; -\(\frac{{aNum}}{{aDen}}\)</span></p>

            </td>
            <td><p><br></p></td>
            <td>
                <p>subtract <span class="" style="color: rgb(255, 51, 102);">\(\frac{{aNum}}{{aDen}}\)<br></span> on both sides</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp;{var}&nbsp; &nbsp; &nbsp; &nbsp;= <span class="" style="color: rgb(51, 102, 255);">&nbsp;{ansW}\(\frac{{redN}}{{redD}}\)&nbsp;</span></p>

            </td>
            <td></td>
            <td>
                <p>simplify</p>
            </td>
        </tr>
        <tr>
            <td colspan="3">
                <div class="editor-indent" style="margin-left: 30px;">
                    <div class="editor-indent" style="margin-left: 30px;">
                        <p style="text-align: left;"><strong>Check</strong></p>
                    </div>
                </div>
            </td>
        </tr>
        <tr>
            <td>

                <p>{var} + \(\frac{{aNum}}{{aDen}}\) = \(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>{ansW}\(\frac{{redN}}{{redD}}\)&nbsp; + \(\frac{{aNum}}{{aDen}}\) ?= \(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>Substitute {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>You can use ?= to show you are testing if the answer is correct.</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>\(\frac{{bNum}}{{bDen}}\) ?= \(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>It is true, therefore {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp; is the correct answer.</p>
            </td>
        </tr>
    </tbody>
</table>

<p dir="ltr" style="text-align: left;"></p>
<p dir="ltr"></p>
<h5><strong><span class="" style="color: rgb(255, 51, 102);">Directions for Subtracting the Fractions:</span></strong></h5><h5>1.&nbsp; The least common multiple of {number1} and {number2} is&nbsp;<strong>{least}</strong></h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">The multiples of {number1} are: {multiples1}</p>
    <p dir="ltr">The multiples of {number2} are: {multiples2}</p>
</div>
<h5>2.&nbsp; &nbsp;Use the&nbsp;identity property of multiplication: A number multiplied by one equals the number.&nbsp; (7 • 1 = 7)</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <table>
        <tbody>
            <tr>
                <td>
                    <p>\(\frac{{factor0}}{{factor0}}\) = 1</p>
                    <p>\( \frac{{num0}}{{den0}} \)&nbsp;•&nbsp;\(\frac{{factor0}}{{factor0}}\)&nbsp;=&nbsp;\( \frac{{ansNum0}}{{ansDen0}} \)</p>
                </td>
                <td>&nbsp; &nbsp; &nbsp;</td>
                <td>
                    <p>\(\frac{{factor1}}{{factor1}}\) = 1</p>
                    <p>\( \frac{{num1}}{{den1}} \)&nbsp;•&nbsp;\(\frac{{factor1}}{{factor1}}\)&nbsp;=&nbsp;\( \frac{{ansNum1}}{{ansDen1}} \)</p>
                </td>
            </tr>
        </tbody>
    </table>
    <p></p>
</div>
<h5>3.&nbsp; Calculate the {answer}.</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">{opWord} the numerators:&nbsp; {ansNum0}{opSign}{ansNum1} = {impN}&nbsp;</p>
    <p dir="ltr">Keep the denominator:&nbsp; {least}</p>
    <p dir="ltr">The sum of the fractions is \(\frac{{impN}}{{least}}\)</p>
</div>
<p dir="ltr"></p>
<h5>4.&nbsp; Write the answer in simplest form.</h5>
<div><br>

</div>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr"><span style="font-size: 0.9375rem;">{FB1}</span></p>
    <p dir="ltr">The fractional part is \(\frac{{ansN}}{{ansD}}\)</p>
    <p dir="ltr">Determine the GCF of the numerator and denominator:</p>
    <p dir="ltr">The factors of {ansN}: {=FB[ansN]}</p>
    <p dir="ltr">The factors of {ansD}: {=FB[ansD]}</p>
    <p dir="ltr">The GCF (greatest common factor) of {ansN} and {ansD} is {gcfND}.</p>
    <table>
        <tbody>
            <tr>
                <td style="border-bottom: 1px solid black">{ansN}</td>
                <td rowspan="2">÷<br></td>
                <td style="border-bottom: 1px solid black">{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{ansN}÷{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{=ansN/gcfND}</td>
            </tr>
            <tr>
                <td>{ansD}</td>
                <td>{gcfND}</td>
                <td>{ansD}÷{gcfND}</td>
                <td>{=ansD/gcfND}</td>
            </tr>
        </tbody>
    </table>
</div>





<br>{ansW}\(\frac{{ansN}}{{ansD}}\) =&nbsp; {ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>
<p></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[var={"x","p","t","c","y","z"};
Tfraction0={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
Tfraction1={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[fractionNums=pick(Tfraction0[0]/Tfraction0[1]>Tfraction1[0]/Tfraction1[1],[Tfraction0[0],Tfraction0[1],Tfraction1[0],Tfraction1[1]],[Tfraction1[0],Tfraction1[1],Tfraction0[0],Tfraction0[1]]);

aNum=fractionNums[0];
aDen=fractionNums[1];
bNum=fractionNums[2];
bDen=fractionNums[3];
y={-100:100:1};
z={-100:100:1};
t={-100:100:1};
p={-100:100:1};
c={-100:100:1};
randOp=0;
opSign=pick(randOp," - "," + ");
opWord=pick(randOp,"Subtract","Add");
frac0=Tfraction0[0]/Tfraction0[1];
frac1=Tfraction1[0]/Tfraction1[1];
fraction0=pick(frac0 >frac1,Tfraction1,Tfraction0);
fraction1=pick(frac0 >frac1,Tfraction0,Tfraction1);
numbers=[fraction0[1],fraction1[1]];
number1=numbers[0];
number2=numbers[1];
operation=pick(randOp,"-","+");
answer=pick(randOp,"difference","sum");
least=lcm(number1,number2);

multiples1=pick(number1==least,join("",number1),join("","<b>",number1,"</b>"));
multiples2=pick(number2==least,join("",number2),join("","<b>",number2,"</b>"));
for(i:[2:11]){
multiples1=pick(number1*i == least,join("",multiples1,", ",number1*i),join("",multiples1,", <b>",number1*i,"</b>"));

multiples2=pick(number2*i == least,join("",multiples2,", ",number2*i),join("",multiples2,", <b>",number2*i,"</b>"));
}

num0=fraction0[0];
den0=fraction0[1];
ansNum0=num0*(least/den0);
ansDen0=least;
factor0=least/den0;

num1=fraction1[0];
den1=fraction1[1];
ansNum1=num1*(least/den1);
ansDen1=least;
factor1=least/den1;

ansN=pick(randOp,ansNum0-ansNum1,ansNum0+ansNum1);
impN=ansN;
ansD=least;
ansW=floor(ansN/ansD);
ansN=ansN-(ansW*ansD);

FB1=pick(impN>ansN,"The numerator is less than the denominator.  The whole number is 0.",join("","The numerator is larger than the denominator.<br> Determine how many times the denominator can divide into the numerator.<br>",impN,"/",least," = ",ansW," with ",ansN," left over. <br>Put the left over amount in the numerator and keep the same denominator."));
gcfND=gcd(ansN,ansD);
redN=ansN/gcfND;
redD=ansD/gcfND;
FB=["0","1","1 2","1 3","1 2 4","1 5","1 2 3 6","1 7","1 2 4 8","1 3 9","1 2 5 10","1 11","1 2 3 4 6 12","1 13","1 2 7 14","1 3 5 15","1 2 4 8 16","1 17","1 2 3 6 9 18","1 19","1 2 4 5 10 20","1 3 7 21","1 2 11 22","1 23","1 2 3 4 6 8 12 24","1 5 25","1 2 13 26","1 3 9 27","1 2 4 7 14 28","1 29","1 2 3 5 6 10 15 30","1 31","1 2 4 8 16 32","1 3 11 33","1 2 17 34","1 5 7 35","1 2 3 4 6 9 12 18 36","1 37","1 2 19 38","1 3 13 39","1 2 4 5 8 10 20 40","1 41","1 2 3 6 7 14 21 42","1 43","1 2 4 11 22 44","1 3 5 9 15 45","1 2 23 46","1 47","1 2 3 4 6 8 12 16 24 48","1 7 49","1 2 5 10 25 50","1 3 17 51","1 2 4 13 26 52","1 53","1 2 3 6 9 18 27 54","1 5 11 55","1 2 4 7 8 14 28 56","1 3 19 57","1 2 29 58","1 59","1 2 3 4 5 6 10 12 15 20 30 60","1 61","1 2 31 62","1 3 7 9 21 63","1 2 4 8 16 32 64","1 5 13 65","1 2 3 6 11 22 33 66","1 67","1 2 4 17 34 68","1 3 23 69","1 2 5 7 10 14 35 70","1 71","1 2 3 4 6 8 9 12 18 24 36 72","1 73","1 2 37 74","1 3 5 15 25 75","1 2 4 19 38 76","1 7 11 77","1 2 3 6 13 26 39 78","1 79","1 2 4 5 8 10 16 20 40 80","1 3 9 27 81","1 2 41 82","1 83","1 2 3 4 6 7 12 14 21 28 42 84","1 5 17 85","1 2 43 86","1 3 29 87","1 2 4 8 11 22 44 88","1 89","1 2 3 5 6 9 10 15 18 30 45 90","1 7 13 91","1 2 4 23 46 92","1 3 31 93","1 2 47 94","1 5 19 95","1 2 3 4 6 8 12 16 24 32 48 96","1 97","1 2 7 14 49 98","1 3 9 11 33 99","1 2 4 5 10 20 25 50 100"];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>3</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[ansW,redN,redD]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>((redN/redD ==_1/_2)*.5)+(((gcd(redN,redD)) ==1)*.5)</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table>
    <tbody>
        <tr>
            <td rowspan="2">{var}=</td>
            <td rowspan="2">{_0}</td>
            <td style="border-bottom:1px solid black">{_1}</td>
        </tr>
        <tr>
            <td>{_2}</td>
        </tr>
    </tbody>
</table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360952  -->
  <question type="formulas">
    <name>
      <text>TL60 - Subtraction Equation Mixed Numbers</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Solve for {var}:</h3>
<h3 style="text-align: left;">{var} - {whole1}\(\frac{{aNum}}{{aDen}}\) = {whole2}\(\frac{{bNum}}{{bDen}}\)</h3>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><table>
    <tbody>
        <tr>
            <td>
                <p>{var} - {whole1}\(\frac{{aNum}}{{aDen}}\) = {whole2}\(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td><p>&nbsp; &nbsp; &nbsp; &nbsp;</p></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp; <span class="" style="color: rgb(255, 51, 102);">+{whole1}\(\frac{{aNum}}{{aDen}}\)&nbsp; &nbsp; +{whole1}\(\frac{{aNum}}{{aDen}}\)</span></p>

            </td>
            <td><p><br></p></td>
            <td>
                <p>add&nbsp;<span class="" style="color: rgb(255, 51, 102);">{whole1}\(\frac{{aNum}}{{aDen}}\)<br></span> to both sides</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp;{var}&nbsp; &nbsp; &nbsp; &nbsp;= <span class="" style="color: rgb(51, 102, 255);">&nbsp;{ansW}\(\frac{{redN}}{{redD}}\)&nbsp;</span></p>

            </td>
            <td></td>
            <td>
                <p>simplify</p>
            </td>
        </tr>
        <tr>
            <td colspan="3">
                <div class="editor-indent" style="margin-left: 30px;">
                    <div class="editor-indent" style="margin-left: 30px;">
                        <p style="text-align: left;"><strong>Check</strong></p>
                    </div>
                </div>
            </td>
        </tr>
        <tr>
            <td>

                <p>{var} - {whole1}\(\frac{{aNum}}{{aDen}}\) = {whole2}\(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>{ansW}\(\frac{{redN}}{{redD}}\)&nbsp; - {whole1}\(\frac{{aNum}}{{aDen}}\) ?= {whole2}\(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>Substitute {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>You can use ?= to show you are testing if the answer is correct.</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>{ansW}\(\frac{{bNum}}{{bDen}}\) ?= {ansW}\(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>It is true, therefore {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp; is the correct answer.</p>
            </td>
        </tr>
    </tbody>
</table>

<p dir="ltr" style="text-align: left;"></p>
<p dir="ltr"></p>
<h5><strong><span class="" style="color: rgb(255, 51, 102);">Directions for Subtracting the Fractions:</span></strong></h5><h5>1.&nbsp; The least common multiple of {number1} and {number2} is&nbsp;<strong>{least}</strong></h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">The multiples of {number1} are: {multiples1}</p>
    <p dir="ltr">The multiples of {number2} are: {multiples2}</p>
</div>
<h5>2.&nbsp; &nbsp;Use the&nbsp;identity property of multiplication: A number multiplied by one equals the number.&nbsp; (7 • 1 = 7)</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <table>
        <tbody>
            <tr>
                <td>
                    <p>\(\frac{{factor0}}{{factor0}}\) = 1</p>
                    <p>\( \frac{{num0}}{{den0}} \)&nbsp;•&nbsp;\(\frac{{factor0}}{{factor0}}\)&nbsp;=&nbsp;\( \frac{{ansNum0}}{{ansDen0}} \)</p>
                </td>
                <td>&nbsp; &nbsp; &nbsp;</td>
                <td>
                    <p>\(\frac{{factor1}}{{factor1}}\) = 1</p>
                    <p>\( \frac{{num1}}{{den1}} \)&nbsp;•&nbsp;\(\frac{{factor1}}{{factor1}}\)&nbsp;=&nbsp;\( \frac{{ansNum1}}{{ansDen1}} \)</p>
                </td>
            </tr>
        </tbody>
    </table>
    <p></p>
</div>
<h5>3.&nbsp; Calculate the {answer}.</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">{opWord} the numerators:&nbsp; {ansNum0}{opSign}{ansNum1} = {impN}&nbsp;</p>
    <p dir="ltr">Keep the denominator:&nbsp; {least}</p>
    <p dir="ltr">The sum of the fractions is \(\frac{{impN}}{{least}}\)</p>
</div>
<p dir="ltr"></p>
<h5>4.&nbsp; Write the answer in simplest form.</h5>
<div><br>

</div>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr"><span style="font-size: 0.9375rem;">{FB1}</span></p>
    <p dir="ltr">The fractional part is \(\frac{{ansN}}{{ansD}}\)</p>
    <p dir="ltr">Determine the GCF of the numerator and denominator:</p>
    <p dir="ltr">The factors of {ansN}: {=FB[ansN]}</p>
    <p dir="ltr">The factors of {ansD}: {=FB[ansD]}</p>
    <p dir="ltr">The GCF (greatest common factor) of {ansN} and {ansD} is {gcfND}.</p>
    <table>
        <tbody>
            <tr>
                <td style="border-bottom: 1px solid black">{ansN}</td>
                <td rowspan="2">÷<br></td>
                <td style="border-bottom: 1px solid black">{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{ansN}÷{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{=ansN/gcfND}</td>
            </tr>
            <tr>
                <td>{ansD}</td>
                <td>{gcfND}</td>
                <td>{ansD}÷{gcfND}</td>
                <td>{=ansD/gcfND}</td>
            </tr>
        </tbody>
    </table>
</div>





<br>{ansW}\(\frac{{ansN}}{{ansD}}\) =&nbsp; {ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>
<p></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[var={"x","p","t","c","y","z"};
whole1={1:4:1};
whole2={5:9:1};
Tfraction0={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
Tfraction1={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[temp=whole1;

fractionNums=pick(Tfraction0[0]/Tfraction0[1]>Tfraction1[0]/Tfraction1[1],[Tfraction0[0],Tfraction0[1],Tfraction1[0],Tfraction1[1]],[Tfraction1[0],Tfraction1[1],Tfraction0[0],Tfraction0[1]]);

aNum=fractionNums[0];
aDen=fractionNums[1];
bNum=fractionNums[2];
bDen=fractionNums[3];
y={-100:100:1};
z={-100:100:1};
t={-100:100:1};
p={-100:100:1};
c={-100:100:1};
randOp=1;
opSign=pick(randOp," - "," + ");
opWord=pick(randOp,"Subtract","Add");
frac0=Tfraction0[0]/Tfraction0[1];
frac1=Tfraction1[0]/Tfraction1[1];
fraction0=pick(frac0 >frac1,Tfraction1,Tfraction0);
fraction1=pick(frac0 >frac1,Tfraction0,Tfraction1);
numbers=[fraction0[1],fraction1[1]];
number1=numbers[0];
number2=numbers[1];
operation=pick(randOp,"-","+");
answer=pick(randOp,"difference","sum");
least=lcm(number1,number2);

multiples1=pick(number1==least,join("",number1),join("","<b>",number1,"</b>"));
multiples2=pick(number2==least,join("",number2),join("","<b>",number2,"</b>"));
for(i:[2:11]){
multiples1=pick(number1*i == least,join("",multiples1,", ",number1*i),join("",multiples1,", <b>",number1*i,"</b>"));

multiples2=pick(number2*i == least,join("",multiples2,", ",number2*i),join("",multiples2,", <b>",number2*i,"</b>"));
}

num0=fraction0[0];
den0=fraction0[1];
ansNum0=num0*(least/den0);
ansDen0=least;
factor0=least/den0;

num1=fraction1[0];
den1=fraction1[1];
ansNum1=num1*(least/den1);
ansDen1=least;
factor1=least/den1;

ansN=pick(randOp,ansNum0-ansNum1,ansNum0+ansNum1);
impN=ansN;
ansD=least;
ansW=floor(ansN/ansD);
ansN=ansN-(ansW*ansD);

FB1=pick(impN>ansN,join("","The numerator is less than the denominator.  The whole number is ",whole2+whole1," (because ",whole2," + ",whole1," is ",whole2+whole1,")."),join("","The numerator is larger than the denominator.<br> Determine how many times the denominator can divide into the numerator.<br>",impN,"/",least," = ",ansW," with ",ansN," left over. <br>Put the left over amount in the numerator and keep the same denominator.<br> The whole number is ",ansW+whole2+whole1," (because the whole numbers need to be added included: ",whole2," + ",whole1," is ",whole2+whole1,")."));
ansW=ansW+(whole2+whole1);
gcfND=gcd(ansN,ansD);
redN=ansN/gcfND;
redD=ansD/gcfND;
FB=["0","1","1 2","1 3","1 2 4","1 5","1 2 3 6","1 7","1 2 4 8","1 3 9","1 2 5 10","1 11","1 2 3 4 6 12","1 13","1 2 7 14","1 3 5 15","1 2 4 8 16","1 17","1 2 3 6 9 18","1 19","1 2 4 5 10 20","1 3 7 21","1 2 11 22","1 23","1 2 3 4 6 8 12 24","1 5 25","1 2 13 26","1 3 9 27","1 2 4 7 14 28","1 29","1 2 3 5 6 10 15 30","1 31","1 2 4 8 16 32","1 3 11 33","1 2 17 34","1 5 7 35","1 2 3 4 6 9 12 18 36","1 37","1 2 19 38","1 3 13 39","1 2 4 5 8 10 20 40","1 41","1 2 3 6 7 14 21 42","1 43","1 2 4 11 22 44","1 3 5 9 15 45","1 2 23 46","1 47","1 2 3 4 6 8 12 16 24 48","1 7 49","1 2 5 10 25 50","1 3 17 51","1 2 4 13 26 52","1 53","1 2 3 6 9 18 27 54","1 5 11 55","1 2 4 7 8 14 28 56","1 3 19 57","1 2 29 58","1 59","1 2 3 4 5 6 10 12 15 20 30 60","1 61","1 2 31 62","1 3 7 9 21 63","1 2 4 8 16 32 64","1 5 13 65","1 2 3 6 11 22 33 66","1 67","1 2 4 17 34 68","1 3 23 69","1 2 5 7 10 14 35 70","1 71","1 2 3 4 6 8 9 12 18 24 36 72","1 73","1 2 37 74","1 3 5 15 25 75","1 2 4 19 38 76","1 7 11 77","1 2 3 6 13 26 39 78","1 79","1 2 4 5 8 10 16 20 40 80","1 3 9 27 81","1 2 41 82","1 83","1 2 3 4 6 7 12 14 21 28 42 84","1 5 17 85","1 2 43 86","1 3 29 87","1 2 4 8 11 22 44 88","1 89","1 2 3 5 6 9 10 15 18 30 45 90","1 7 13 91","1 2 4 23 46 92","1 3 31 93","1 2 47 94","1 5 19 95","1 2 3 4 6 8 12 16 24 32 48 96","1 97","1 2 7 14 49 98","1 3 9 11 33 99","1 2 4 5 10 20 25 50 100"];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>3</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[ansW,redN,redD]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>((_0==ansW)*.4)+((redN/redD ==_1/_2)*.3)+(((gcd(redN,redD)) ==1)*.3)</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table>
    <tbody>
        <tr>
            <td rowspan="2">{var}=</td>
            <td rowspan="2">{_0}</td>
            <td style="border-bottom:1px solid black">{_1}</td>
        </tr>
        <tr>
            <td>{_2}</td>
        </tr>
    </tbody>
</table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360953  -->
  <question type="formulas">
    <name>
      <text>TL60 - Subtraction Equation with Fraction</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Solve for {var}:</h3>
<h3 style="text-align: left;">{var} - \(\frac{{aNum}}{{aDen}}\) = \(\frac{{bNum}}{{bDen}}\)</h3>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><table>
    <tbody>
        <tr>
            <td>
                <p>{var} -
                    \(\frac{{aNum}}{{aDen}}\) = \(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td><p>&nbsp; &nbsp; &nbsp; &nbsp;</p></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp;<span class="" style="color: rgb(255, 51, 102);">+</span><span class="" style="color: rgb(255, 51, 102);">&nbsp;\(\frac{{aNum}}{{aDen}}\)&nbsp; &nbsp; +\(\frac{{aNum}}{{aDen}}\)</span></p>

            </td>
            <td><p><br></p></td>
            <td>
                <p>add&nbsp;<span class="" style="color: rgb(255, 51, 102);">\(\frac{{aNum}}{{aDen}}\)<br></span> to both sides</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>&nbsp;{var}&nbsp; &nbsp; &nbsp; &nbsp;= <span class="" style="color: rgb(51, 102, 255);">&nbsp;{ansW}\(\frac{{redN}}{{redD}}\)&nbsp;</span></p>

            </td>
            <td></td>
            <td>
                <p>simplify</p>
            </td>
        </tr>
        <tr>
            <td colspan="3">
                <div class="editor-indent" style="margin-left: 30px;">
                    <div class="editor-indent" style="margin-left: 30px;">
                        <p style="text-align: left;"><strong>Check</strong></p>
                    </div>
                </div>
            </td>
        </tr>
        <tr>
            <td>

                <p>{var} - \(\frac{{aNum}}{{aDen}}\) = \(\frac{{bNum}}{{bDen}}\)</p>

            </td>
            <td></td>
            <td>
                <p>Write the equation</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>{ansW}\(\frac{{redN}}{{redD}}\)&nbsp; + \(\frac{{aNum}}{{aDen}}\) ?= \(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>Substitute {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>You can use ?= to show you are testing if the answer is correct.</p>
            </td>
        </tr>
        <tr>
            <td>
                <p>\(\frac{{bNum}}{{bDen}}\) ?= \(\frac{{bNum}}{{bDen}}\)</p>
            </td>
            <td></td>
            <td>
                <p>It is true, therefore {var}={ansW}\(\frac{{redN}}{{redD}}\)&nbsp; is the correct answer.</p>
            </td>
        </tr>
    </tbody>
</table>

<p dir="ltr" style="text-align: left;"></p>
<p dir="ltr"></p>
<h5><strong><span class="" style="color: rgb(255, 51, 102);">Directions for Subtracting the Fractions:</span></strong></h5><h5>1.&nbsp; The least common multiple of {number1} and {number2} is&nbsp;<strong>{least}</strong></h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">The multiples of {number1} are: {multiples1}</p>
    <p dir="ltr">The multiples of {number2} are: {multiples2}</p>
</div>
<h5>2.&nbsp; &nbsp;Use the&nbsp;identity property of multiplication: A number multiplied by one equals the number.&nbsp; (7 • 1 = 7)</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <table>
        <tbody>
            <tr>
                <td>
                    <p>\(\frac{{factor0}}{{factor0}}\) = 1</p>
                    <p>\( \frac{{num0}}{{den0}} \)&nbsp;•&nbsp;\(\frac{{factor0}}{{factor0}}\)&nbsp;=&nbsp;\( \frac{{ansNum0}}{{ansDen0}} \)</p>
                </td>
                <td>&nbsp; &nbsp; &nbsp;</td>
                <td>
                    <p>\(\frac{{factor1}}{{factor1}}\) = 1</p>
                    <p>\( \frac{{num1}}{{den1}} \)&nbsp;•&nbsp;\(\frac{{factor1}}{{factor1}}\)&nbsp;=&nbsp;\( \frac{{ansNum1}}{{ansDen1}} \)</p>
                </td>
            </tr>
        </tbody>
    </table>
    <p></p>
</div>
<h5>3.&nbsp; Calculate the {answer}.</h5>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr">{opWord} the numerators:&nbsp; {ansNum0}{opSign}{ansNum1} = {impN}&nbsp;</p>
    <p dir="ltr">Keep the denominator:&nbsp; {least}</p>
    <p dir="ltr">The sum of the fractions is \(\frac{{impN}}{{least}}\)</p>
</div>
<p dir="ltr"></p>
<h5>4.&nbsp; Write the answer in simplest form.</h5>
<div><br>

</div>
<div class="editor-indent" style="margin-left: 30px;">
    <p dir="ltr"><span style="font-size: 0.9375rem;">{FB1}</span></p>
    <p dir="ltr">The fractional part is \(\frac{{ansN}}{{ansD}}\)</p>
    <p dir="ltr">Determine the GCF of the numerator and denominator:</p>
    <p dir="ltr">The factors of {ansN}: {=FB[ansN]}</p>
    <p dir="ltr">The factors of {ansD}: {=FB[ansD]}</p>
    <p dir="ltr">The GCF (greatest common factor) of {ansN} and {ansD} is {gcfND}.</p>
    <table>
        <tbody>
            <tr>
                <td style="border-bottom: 1px solid black">{ansN}</td>
                <td rowspan="2">÷<br></td>
                <td style="border-bottom: 1px solid black">{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{ansN}÷{gcfND}</td>
                <td rowspan="2">=</td>
                <td style="border-bottom: 1px solid black">{=ansN/gcfND}</td>
            </tr>
            <tr>
                <td>{ansD}</td>
                <td>{gcfND}</td>
                <td>{ansD}÷{gcfND}</td>
                <td>{=ansD/gcfND}</td>
            </tr>
        </tbody>
    </table>
</div>





<br>{ansW}\(\frac{{ansN}}{{ansD}}\) =&nbsp; {ansW}\(\frac{{redN}}{{redD}}\)&nbsp;<br>
<p></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[var={"x","p","t","c","y","z"};
Tfraction0={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
Tfraction1={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[fractionNums=pick(Tfraction0[0]/Tfraction0[1]>Tfraction1[0]/Tfraction1[1],[Tfraction0[0],Tfraction0[1],Tfraction1[0],Tfraction1[1]],[Tfraction1[0],Tfraction1[1],Tfraction0[0],Tfraction0[1]]);

aNum=fractionNums[0];
aDen=fractionNums[1];
bNum=fractionNums[2];
bDen=fractionNums[3];
y={-100:100:1};
z={-100:100:1};
t={-100:100:1};
p={-100:100:1};
c={-100:100:1};
randOp=1;
opSign=pick(randOp," - "," + ");
opWord=pick(randOp,"Subtract","Add");
frac0=Tfraction0[0]/Tfraction0[1];
frac1=Tfraction1[0]/Tfraction1[1];
fraction0=pick(frac0 >frac1,Tfraction1,Tfraction0);
fraction1=pick(frac0 >frac1,Tfraction0,Tfraction1);
numbers=[fraction0[1],fraction1[1]];
number1=numbers[0];
number2=numbers[1];
operation=pick(randOp,"-","+");
answer=pick(randOp,"difference","sum");
least=lcm(number1,number2);

multiples1=pick(number1==least,join("",number1),join("","<b>",number1,"</b>"));
multiples2=pick(number2==least,join("",number2),join("","<b>",number2,"</b>"));
for(i:[2:11]){
multiples1=pick(number1*i == least,join("",multiples1,", ",number1*i),join("",multiples1,", <b>",number1*i,"</b>"));

multiples2=pick(number2*i == least,join("",multiples2,", ",number2*i),join("",multiples2,", <b>",number2*i,"</b>"));
}

num0=fraction0[0];
den0=fraction0[1];
ansNum0=num0*(least/den0);
ansDen0=least;
factor0=least/den0;

num1=fraction1[0];
den1=fraction1[1];
ansNum1=num1*(least/den1);
ansDen1=least;
factor1=least/den1;

ansN=pick(randOp,ansNum0-ansNum1,ansNum0+ansNum1);
impN=ansN;
ansD=least;
ansW=floor(ansN/ansD);
ansN=ansN-(ansW*ansD);

FB1=pick(impN>ansN,"The numerator is less than the denominator.  The whole number is 0.",join("","The numerator is larger than the denominator.<br> Determine how many times the denominator can divide into the numerator.<br>",impN,"/",least," = ",ansW," with ",ansN," left over. <br>Put the left over amount in the numerator and keep the same denominator."));
gcfND=gcd(ansN,ansD);
redN=ansN/gcfND;
redD=ansD/gcfND;
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<answernumbering><text>abc</text>
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<text><![CDATA[<table>
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            <td rowspan="2">{var}=</td>
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<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L61-Algebraic Expressions with Fractions</text>
    </category>
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      <text></text>
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<!-- question: 360992  -->
  <question type="formulas">
    <name>
      <text>L61- a + b(c+d)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<p style="text-align: left;">{a} + {b}({cWhole}\(\frac{{cNum}}{{cDen}}\) + {dWhole}\(\frac{{dNum}}{{dDen}}\))</p>
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      <text><![CDATA[<table>
    <tbody>
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                <p>{a} + {b}(<span class="" style="color: rgb(255, 51, 102);">{cWhole}\(\frac{{cNum}}{{cDen}}\) + {dWhole}\(\frac{{dNum}}{{dDen}}\)</span>)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(255, 51, 102);">({cWhole}\(\frac{{cNum}}{{cDen}}\) + {dWhole}\(\frac{{dNum}}{{dDen}}\))</span></span></p>Add the fractions:&nbsp; \(\frac{{cNum}}{{cDen}}\) + \(\frac{{dNum}}{{dDen}}\) = \(\frac{{=cNum+dNum}}{{cDen}}\) = 1<br><br>Add the whole numbers:&nbsp;{cWhole} + {dWhole} = {=cWhole+dWhole}<br><br></td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
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            <td>
                <p>{a} + <span class="" style="color: rgb(51, 102, 255);">{b}({=c+d})</span></p>
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            <td></td>
            <td>
                <p><span>Multiply {b}({=c+d})</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></p>
            </td>
            <td></td>
            <td>
                <p>Add <span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
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        <tr>
            <td>
                <p>{ans}</p>
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</table>]]></text>
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</file>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={-11:11:1};
b={-11:11:1};
cWhole={1:11:1};
dWhole={1:11:1};
TfractionD={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};</text>
</varsrandom>
<varsglobal><text>dNum=TfractionD[0];
dDen=TfractionD[1];
cNum=dDen-TfractionD[0];
dDen=TfractionD[1];
cDen=dDen;
c=cWhole+cNum/cDen;
d=dWhole+dNum/dDen;
ans = a + b*(c+d);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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 <answer>
  <text>ans</text>
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  <text></text>
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  <text>1</text>
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<text></text>
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 <feedback format="html">
<text></text>
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<text></text>
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<text></text>
 </partiallycorrectfeedback>
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<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360990  -->
  <question type="formulas">
    <name>
      <text>L61- a b - c (d - e) + f</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p style="text-align: left;">Evaluate the expression if a=\(\frac{{aNum}}{{aDen}}\), b={b}, and c = {f}<br>ab<span style="font-size: 19.6875px;">&nbsp;-&nbsp;</span>&nbsp;{c}({d} - {e}) + c</p>

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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p>
    <tdp>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</tdp>
</p>
<table>
    <tbody>
        <tr>
            <td>
                <p>ab&nbsp;-&nbsp;&nbsp;{c}(<span>{d} - {e}</span>) + c</p>
            </td>
            <td></td>
            <td>Substitute the values of the variable:<br>
                <p>a=\(\frac{{aNum}}{{aDen}}\),&nbsp; b={b}, and c = {f}</p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p>\(\frac{{aNum}}{{aDen}}\) ({b}) -&nbsp;&nbsp;{c}(<span class="" style="color: rgb(255, 51, 102);">{d} - {e}</span>) + {f}</p>

            </td>
            <td></td>
            <td>
                <p><span>Parentheses:&nbsp; {d} - {e}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);">\(\frac{{aNum}}{{aDen}}\)({b})</span>&nbsp;-&nbsp;&nbsp;{c}({=d-e}) + {f}</p>
            </td>
            <td>

            </td>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);">
                    </span></p>
                <p><span class="" style="color: rgb(51, 51, 51);">Multiply&nbsp;</span>\(\frac{{aNum}}{{aDen}}\)({b})</p>
                <p></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{=a*b}&nbsp;-&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{c}({=d-e})</span> + {f}</p>

            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p>Multiply <span class="" style="color: rgb(51, 255, 102);">{c}({=d-e})</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(255, 204, 51);">{=a*b}&nbsp;-&nbsp;&nbsp;{=c*(d-e)} </span>+ {f}</p>

            </td>
            <td>

            </td>
            <td>
                <p>Subtract&nbsp; <span class="" style="color: rgb(255, 204, 51);">{=a/b}&nbsp;- {=c*(d-e)}</span></p>
            </td>
            <td style="text-align: left;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr> </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(204, 51, 255);">{=a*b-(c*(d-e))} </span><span class="" style="color: rgb(204, 51, 255);">+ {f}</span></p>

            </td>
            <td></td>
            <td>
                <p>Add <span class="" style="color: rgb(204, 51, 255);">{=a*b-(c*(d-e))} + {f}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
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</file>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>TfractionA={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};

b={1:3:1};
c={1:5:1};
d={1:5:1};
e={1:10:1};
f={1:10:1};</text>
</varsrandom>
<varsglobal><text>d=d+e;
aNum=TfractionA[0];
aDen=TfractionA[1];
a=aNum/aDen;
b=b*aDen;
ans = a*b - c*(d-e) + f;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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 <answer>
  <text>ans</text>
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  <text></text>
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<text></text>
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 <feedback format="html">
<text></text>
 </feedback>
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<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
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<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360997  -->
  <question type="formulas">
    <name>
      <text>L61- a b - c (d - e) + f</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p style="text-align: left;">Evaluate the expression if a=\(\frac{{aNum}}{{aDen}}\), b={b}, and c = {f}<br>ab<span style="font-size: 19.6875px;">&nbsp;-&nbsp;</span>&nbsp;{c}({d} - {e}) + c</p>

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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p>
    <tdp>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</tdp>
</p>
<table>
    <tbody>
        <tr>
            <td>
                <p>ab&nbsp;-&nbsp;&nbsp;{c}(<span>{d} - {e}</span>) + c</p>
            </td>
            <td></td>
            <td>Substitute the values of the variable:<br>
                <p>a=\(\frac{{aNum}}{{aDen}}\),&nbsp; b={b}, and c = {f}</p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p>\(\frac{{aNum}}{{aDen}}\) ({b}) -&nbsp;&nbsp;{c}(<span class="" style="color: rgb(255, 51, 102);">{d} - {e}</span>) + {f}</p>

            </td>
            <td></td>
            <td>
                <p><span>Parentheses:&nbsp; {d} - {e}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);">\(\frac{{aNum}}{{aDen}}\)({b})</span>&nbsp;-&nbsp;&nbsp;{c}({=d-e}) + {f}</p>
            </td>
            <td>

            </td>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);">
                    </span></p>
                <p><span class="" style="color: rgb(51, 51, 51);">Multiply&nbsp;</span>{a}({b})</p>
                <p></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{=a*b}&nbsp;-&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{c}({=d-e})</span> + {f}</p>

            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p>Multiply <span class="" style="color: rgb(51, 255, 102);">{c}({=d-e})</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(255, 204, 51);">{=a*b}&nbsp;-&nbsp;&nbsp;{=c*(d-e)} </span>+ {f}</p>

            </td>
            <td>

            </td>
            <td>
                <p>Subtract&nbsp; <span class="" style="color: rgb(255, 204, 51);">{=a/b}&nbsp;- {=c*(d-e)}</span></p>
            </td>
            <td style="text-align: left;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr> </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(204, 51, 255);">{=a*b-(c*(d-e))} </span><span class="" style="color: rgb(204, 51, 255);">+ {f}</span></p>

            </td>
            <td></td>
            <td>
                <p>Add <span class="" style="color: rgb(204, 51, 255);">{=a*b-(c*(d-e))} + {f}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>TfractionA={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};

b={1:3:1};
c={1:5:1};
d={1:5:1};
e={1:10:1};
f={1:10:1};</text>
</varsrandom>
<varsglobal><text>d=d+e;
aNum=TfractionA[0];
aDen=TfractionA[1];
a=aNum/aDen;
b=b*aDen;
ans = a*b - c*(d-e) + f;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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 <vars1>
  <text></text>
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 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
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  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
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 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360991  -->
  <question type="formulas">
    <name>
      <text>L61- Aa/b</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if a={a}, b={b}, and c={c}</h3>
<h3 style="text-align: left;">\(\frac{{A}a}{c}\)</h3>
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <h3></h3>
                <h3></h3>
                <h3>\(\frac{{A}a}{c}\)</h3><span class="" style="color: rgb(255, 51, 102);"></span>
            </td>
            <td>
            </td>
            <td>
                <h3>Substitute the value of each variable:</h3>
                <h3><span class="" style="color: rgb(255, 51, 102);">a={a}, b={b}, and c={c}</span></h3>
            </td>
            <td>
            </td>
        </tr>

        <tr>
            <td>
                <h3></h3>
                <h3></h3>
                <h3></h3><h3>\(\frac{<span class="" style="color: rgb(255, 51, 102);">{A}({a})</span>}{{c}}\)</h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <h3>{A}a means {A} times a, therefore&nbsp;</h3>
                <h3>parentheses are used around&nbsp;</h3>
                <h3>the number being substituted.</h3><p></p><h3><span>Multiply&nbsp;<span class="" style="color: rgb(255, 51, 102);">{A}({a})</span></span></h3><br><p></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <h3></h3>
                <h3></h3>
                <h3><span class="" style="color: rgb(51, 102, 255);"></span></h3>
                <h3><span class="" style="color: rgb(51, 102, 255);">\(\frac{{=A*a}}{{c}}\)</span></h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <h3></h3><h3><span>Divide&nbsp;<span class="" style="color: rgb(51, 102, 255);">{=A*a}({c})</span></span></h3>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <h3>{ans}</h3>
                <h3></h3>
                <h3><span class="" style="color: rgb(51, 102, 255);"></span></h3>
                <h3></h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <h3><span>
                        <h3><br></h3>
                    </span></h3>
            </td>
            <td style="text-align: center;"><br></td>
        </tr>
        
    </tbody>
</table><br>]]></text>
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</file>
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    <shownumcorrect/>
<varsrandom><text>a={8:16:1};
b={1:6:1};
A={8:16:1};
c={1:10:1};</text>
</varsrandom>
<varsglobal><text>A=A*c;
ans=A*a/c;</text>
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<answernumbering><text>abc</text>
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<!-- question: 360996  -->
  <question type="formulas">
    <name>
      <text>L61- Aa/b (three fractions)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p style="text-align: left;">Evaluate the expression if a=\(\frac{{aNum}}{{aDen}}\), b=\(\frac{{=aDen-aNum}}{{aDen}}\), and c=\(\frac{{c}}{{aDen}}\)<br></p><h3>\(\frac{{A}a}{c}\)</h3><p></p>

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      <text><![CDATA[<table>
    <tbody>
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            <td>
                <p></p>
                <p></p>
                <p>\(\frac{{A}a}{c}\)</p><span class="" style="color: rgb(255, 51, 102);"></span>
            </td>
            <td>
            </td>
            <td>
                <p>Substitute the value of each variable:</p>
                <p><span class="" style="color: rgb(255, 51, 102);">a=\(\frac{{aNum}}{{aDen}}\)</span></p>
            </td>
            <td>
            </td>
        </tr>

        <tr>
            <td>
                <p></p>
                <p></p>
                <p></p>
                <p>\(  \frac{ ({A})(\frac{{aNum}}{{aDen}})}{{c}}  \)<br></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p>{A}a means {A} times a, therefore&nbsp;</p>
                <p>parentheses are used around&nbsp;<span style="font-size: 0.9375rem;">the number being substituted.</span></p>
                <p></p>
                <p><span>Multiply&nbsp;<span class="" style="color: rgb(255, 51, 102);">{A}(\(\frac{{aNum}}{{aDen}}\)) = <span class="" style="color: rgb(51, 102, 255);">{=A*a}</span></span></span></p><br>
                <p></p>
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            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"><br></td>
        </tr>
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                <p></p>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">\(\frac{{=A*a}}{{c}}\)</span></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p></p>
                <p><span>Divide&nbsp;<span class="" style="color: rgb(51, 102, 255);">{=A*a}÷{c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
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                <p>{ans}</p>
                <p></p>
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                <p></p>
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            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
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                        </span></p><p><br></p>
                    <p></p>
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</file>
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j2sfT9CLLBDy8GP9ykxYVFhgWHeCmX9X2Awf5l2IeWZdk/5qN/LjL2mjtVWOXwIP7O2M6tccVubq1pEmbN5OYQV2spR5FD15y6h7vwsZtDrY2Y/+zDbrUTtnKrn7eTW/OaSW4tCcfKdmqxyvfh9/IxI8WyHSNlS9pebD93nHGJKY3VuuJvzdv2cy1BBd+acz4VpnE9Fkn8rXzYJ9yEozZ1R8z+Ufi0Hjz4MeHozdyqp23jVrt0olvjukluzZn7ujVnfyrf3gB88q8vhJr74Ns4YmM3QclsleO2CJ/WY5HE38qHfNytcuwWblWJv9Uv28Wt0bu3W/NW2ZJpZ7h55OOXBssKPPn68271q3bzXOP6SX224f9M+SVmGE/v/0j+XtrtNMlKP0zZ3a0xbU+3xi1aXIiX1L4W60NLsuwj7x/z0T8Vw/hXgXzpc/MZyodX7OrnWy1WcvWlJI5m6TjlqDVu2sutfs0e7pW//znUXI83/u/vbsIxyrtnqp3LlXeV37JrQCvN62U1f2K7DW2XjjMOidJYrSv+Vr/tU64lqMBbfc6+YRrXA/E3/vBPuJWP3tRNOKmjcvLvcO6X3YQTO9wq5+3gVr16N7faLXu71Wftm2+vH35xwRmhxnqcd/e1brzE38pHbuImnLBl+LQe3tZDPuZWPnZzN+H0bdyql010q/Uqad26T7atYaV8+u3HLwmWFXjytefcKufu4Lnq5bLt+j3cajfLPu//Uvkl5MwX53vxDG/9/X1utZv2LEg7M+WH2YMfkyEx54dXgx/O39Gt2rOrt2/1GYqX4IdTnrq+1of5f3rC/evsg4s+xLGkD0vJX8sd1W/myCOv/87755E/P+2+MP/Uwj/T9+qbdyM9zsZlQ+aBxroKRe7ezE04Q/nwil3catMmDX7+cKxyBznk/CduCTU34qS5F/s1ws/rKTq5Y07HNUB1tMS87s+OEZg/pzyptt9I2p6jtm8sfLAa/iJH44Ph9sM/AaWxWlf8rXLbvq4lKOG3ypx9whSuB4JqnBLIShJ/40/pcFOfuD18U4+fLrzPrfT9zd34M7dxK1+2s5tw0yS3yq1759urouyY/+oTocY+cFY57tCPuZW+vbFb6ZjN3PjTtgrf1MPbKvG30rE65vStCzt69xy8HUuD6ssRJdGz6E+L3fiTtvRc+dzt3YQpuxZ+ku/9GOTqGQTPf2ZmaKkP5z9xc9HOtD3chJvli5nyxVJoq2nm/PCK/HByhxt/6lZu5Qt3dBOu272wTcfuNP/ocFQf7vvj427CVPWB46bLX/RhtnyWa+/NTvnolf97PXimwCv/++dijK/ZzU24Uf6ZsZdbZdY/qX/+2chc1lyoQi13n6F8eMVEnwf83BlsDiCelEcnXL+7e6Pi3j+/BnRt4caftW3RVpJ7d5rf+G7WZTGvK+0Ygfmz0/0VbV+1i5twrXxA27eo7SUZH2MDpbFaV/xN0AC3BHWWM6EigXhBddgn3DglkJV+uJV7/5QDwzf14MEPf4zO/MZfsKNbmQmtsxlfd67NDP/lzv90b2Qe9Pjpovlu3Dc+5sYdtYlb6Qef9MklB28rx0kgriTxN/7Snd3K0/d0E3RGlWtvWKl+H/5YWfQ8K4G8hef4HytB9uziVr5hkpugRFPzkx8LUWeAE0i2EPuVGIvjxHJbodyMF+eHlvow4+l73PhztnfjL58YxkT+oI7Y3nBTbR3+aMkPL8sPWiRWOkFCWCJ45am7FeMkm8rHgkWvSiyet4Mbf/FObuUpOpY+4Jdce8sL8T/jyTgzvpA+8XcaD2Xquxz8GDPviCktIhO0iIzYGBuXHUMcVaGWuzkZJgdwEthffFWR4zWXmacPv/p0qL0ez736Bzfuu8q9WifGX6S5egMnnEUclnMhWBbzOm/HcyMyfw4vnQSDRa+p7R9vJ3+pbYlAPz74gDHK1GFsntJYrSv+xs/Zx7UENanHz947hGM9EFRjD/u4G3v0Jm7cqVu5lS7e0T30ylPh23qce8+1buxxm7txEjYrKZBX0uQfP2vvov5cuyVOef6OUFM9tjv3y27soR9zYyXqsGHc+duHb+qBrWO+8e/FcafL1kt3cuN1RjleZ3K59oaV6vNhj10cLCuA6Bn73U09x+lMfKXLd3YrTdu9zkf3JTufr/zjdbfD3UcWfbh5Tzf+VvVDIjDrT32W89/VD892Y0/4pBt3znZLNCZDpuLqsEczfvie/ECsdCtWrpZdN8ouHfu5X50WjurDQ39Y5MadvKUbd6Z8pjH1fcAfI9WHpczPLTi97iRnxu/vK8YY3hLGmTHKlGX8yydIfmf8RI3xqR1u3AU7uJWu2a2oS/5cXn1kbJKMr2KlCrXcLfGXyzeDImUUn1Oe+VmovRFjdYLu881527uVro1xqJhvkXn9uV9X2DHc8wcfPJhp+8Un3djvKw9qfMZdqLan7lrkAPJ8rh5j05TGal3xN04GtgQVmOP6EX+jlUDGKIGMOW0rN1aT9IQHrw7f1mPRHyW+vhOOu2QnN1aTf5wWsnFKNtl2S0TslEGdtO9t+MEWbqzEAjbk4G2V+Bsj8TdG4o/jxmkSj5P4y7U3rJRPv5kRf2Mk/Dwl/sYqGY9VMvb+YQxUbtEb9Q+7HHr/eW7sFTpOSWGcBNI4JQbGKh6ftvfeO77iFv3l+VBS7b2y2G3Uva8bc/wn3dizt3Njeya6cUqwaXvDTtn6zYz4GyPxN0biz4+nxJ/vG/3SWP30jwvCkc69/Lc/u89c/z035qQtC58prsbhMy0SI9aHpcxvli+D//k5N/bKiQWZMzFmc/3TonDu0zNqAvCN//d3d85917sxWnDH/LDDjdXiNfYaxQp15OLE+OYi49uP+KvlbomLXL4ZNJXPv/nwRaH2Rnzm6qNae15r/tTZ8fdgx3DPH+pRfT996cHQcvDBTcd4f/n1iranqG1yvOzM1mNsmtJYrSv+xs7Z27UEFZRjZ+8VQrIeUfyN9glkKzfmsp3cmJ6d3cv/m3/wY5tzD3ajT9jCjTl3OzfmKi1mN09yY2fumW834QlP5l8iffycC93oI9T+kRu70acoUVy4vW8/hyj+Rh8jYYGtl+7oxk7fw42dMXD7S53y6aGP1SdJRM/o727iOeYM2Xe5BPK03dzYWXsVY6Byi/7aJ97AoXef7cb8eBs35uId3Jipu7ixN6k/yfFpe/7zG3b3/hnTvY0b/YPNa+RvPuf7bPnhouLq0EczfpD4G32cRDp2Xa04uVF26Vg/Vr2Tij6cs60b/cMt3ehjN3OjdWbux1R+8D4jrkaqD0uTsvnQx0v+eHWxG3P2tgU1v8Zep/7JB94f5T7O1GfqOz4bc77mwmkd3o+jj9+imB98do3ihLjPlTe+ucj4aj5XYfRhH+vL3Zl8M2gSf5qjVThk+ql+bo/50db1+aZV5vWymj/UQ32ql/pph/Z8u+RB2eHbJhf6NVPH5uoxNk1prNYVf6Pn7OVaggrK0bPzE3qhBNUoJZAVj97YrXh6h1vx8h3d6KkT3c0v3BuOqMdPnrjPrXjspm7FM3TsZTr2pt3d6BmT8u1Gqv2HXn861NCHl994zY3q/Khb8Vsfdyses4lb8UdbuRWv3MmN1uTJwdv6DR3Psdh66Q5u9PQm2h8Oqk+HlMTfQomeFSX8PPEPvpy2qxs9a89iDFSuLP4O+elZbsWTtnArnr1N0XeOl5hmvMrt+c/o77W7+L6vKGFVI77Q5/57jgvtDTvV1iEl8ef98D354DjFSffWbrQS3ugbdyvsom+MF31Q/Kx43rbFuJ+jPkj4j75652U3pkuDubj402K34imfLHj+dm70FPmDeZPERY18dqv6fr3iQPGw4gXbFf5hjOUrPht9g3x58x5F2ZEaZ+OyIeOrmKhCQ+4u5ZtBM8RfFc6++xq34neS9ohTX0ZshXm9rOZPrIt6qZ+28QHt0r7s8G1jF/ZhZ64eY9OUxmpd8TdKBrYEFZSjtPDmgKBaQQlkBSWQUZrQozShR0l8bX33t8MR9eDBD45dQYJllBayUZrso3p3D20kbSbc+t6jQul69D56p1tBYm4FJZMVjt/cjTp3W7U90Y1SAsvB28rxEn/eVgmeUUooo5RQcu0OK9XXb2TE3woSfnCUxJ/3pfoyShM9+mZhSfx9Y/YZxfE6Mxx1ifqDP5UcfJlMm76v9JnjenbqI39HX1SMw7BQcfWNjPhbQeJvBYm/URJ/oyT+Rkn8cazvlwSgt/U62axFwfvpKv3USccoJU7fB47JtdfqrIoLnTDBUVoIRmkRGDVN/UziIi3vP+/do4gdCUXvH8YYX/GZFhgfIyM5zsZlwxAPVWjI3aV8M2gyRzX3Fv/tj6GFevQ+codb4chPuBVO3bLIv9epPebqrDBnl/W8Xpbzh/qol/pph/Zol/axg8+wayjjY6xRGqt1xV/bnD1dS1ATum12/mwOQdV22L+7tqM/4dpO39K1Xb6Da7t2omu7eXe38PXnwlH16L7nGtemhb3tx1u5tqt2cm037OraNPl9O5n2577cdx9Eio5zDnJth3zUtUnMtZ36Sdd28fZFXTftFo6oh7f1Gx8pjsdWJZ+26bu5thl7NLar/nqbbtV3fA/5fSZ2Vtta+ErkOI6P5fnb91H0x01ynY9dGCwrwCLf9t2NC0r8eV9ev0tRNtS3MLlnD3TOOt21fUe+P2UL13b+toU/6ZP8X2dz9C9/8x1+klCukb/5nO/r+hPKUkdDfcl3fM73t0DVw89c+2ndof7ORzN++J58QIxI/LUpCbbdKPtiexBb+UwLRdsUfU/MTdPv9J02OabcViR2DGR3tD3anbUd6vvKuiLD53W+EMt18bmO6Xz4guCJAnVxcZri9hLF+VT1ubc0zpSPpE18QfxwLGOMrzQ3asem7Zc5YL/CZ2m/KJPzU8pynbFs9Ev6Xa3N8Hs8luPK/lvaTPtfZ0t/Y0q5Uj1l9tf/yPhduY1m/FtmiKsqNORu5lDsS66+gRjaK+epCMRf27c/7tp+qHxNHDNv6RttwoHmdTyWn/gmMn4+kN18H2z09UVfp3VDfD/Y+RPrpZ5Yby1mwt9pW7nxjHbRDu3RLu1jB/ZQvr84KPcvtlmzoyp2xVx9kb5eHRP7Fpn6LO13rc3we11bob5cOyNJE39NMAx8DlnxR9BqwLsX5f/dz8I/qgyCJS5kTHCCg8DItJ97vcuCFxa6tsPV7uEfc23Hb1aIhCt31IKo4BZzaFb89b54XyjhfNtdv5laHAcJZoK4YrLMe/U3oWRRdvL9JxflorDyZXWsyjcj/nqfnxe+HRx6nvlJkUQRCNhM22rz5eQdcJyde9EH8VtpDLqfmRGOdO7lf7xe9IPjguDo/t0Mt+D1p+vGh+MWvPZb1/X4lCKBcXzSfsOkxw+DEX9i2ccddxxRfB/HMiaYtJ1ae0W/qGPx3+t3J1iwep75qeu4U/XFMauqT39PfvCHruf5n3kflHdkAf7FF91P3lz4IhcHqqv9roOzMT4QKBNPdtJ603EDfiyifxiL/vwjtt95cG1sGc8UtImfel+4102en8Q2fkqTe6bedNzwly8b4qnjF0e63j/c1+DHOCbtc75Y6b+lzY77jvLjii3lcYnx3RAnce70Y1M693p/f2+t/+23H+Tm/ek3db6m37U5xHED5J1KYo/sqsIyEX/fUs4+JZysR/EnDjSvO+49sm488Ff7baW4GMD2zscvqqtj3p8eb8hTDXYwzgPNH/3d9eQ1lXll7ou/bmq+ZNtmjtfFQNJuiU3H7l3fqvfbAPVmYzeUn/yrHzb0m7Z97ntKuS/6rskxGjG2tPgLi90yJ4M1a48wrPWoiT/EHAnkMsSfJvQMDbQGvRyAEX7X7gSJtnO0uPdItN2s4CAwSm2XF7KIrtkXFO0eqbNIdr0u3LY4Q6JdBVkO3tZOiT+ExWnhzPMmBSZnQ7FN9XXhG/WJq/fZe1zbFeoX4pK+IahoJ7Ezsrx4dc4/p/DJFHY4lVjpp3zZNnOPvOghEcdkrHJVu6cDYeFri4v+4VsSLP2UzWV42yC+i77w4z2pTgQDvziovs4HzlUiyT/Qk2Lhn59zHbMOlXhT36+XDSQA/Bbq9z6TLxr9oHFCAB8rkc7uMOVJIMFvDT6ed3YxPhzH4kUbOq5ubNRe16Jr6hbY/uDHnPG+JghPxo06RZJ8OcEPBB6A6rxXdl4VxoM68bVivnwSMBj4vl+mcWaXJNiJiErR+0yIX9rGP7Sb8U/7HQer7L2VczYHP8azNcbET9yhyfq/cdy83fJx7+JfhE+qwYuDux7sKXa2o/9y7Swp1X/ERbr4NoO5L/zKtd94YBEnzG9yg19MG/ufgnlN/yffdXzlS5EXvqZjLi181Hat6p8eYibOnWbIsbKlCm3f/Gh97maeYvtg2khJOca6Svw9/DPXdoTE38mlnH3r7gPPa/W9HJvdj08P8a9j0vxaYX95fOe99FhRvpajdm20g3lbNX/UDieBzeaDBX96yrXfkMRLzCvB3uz6QQxEHxBfmf51zFsKsYst5fwcmMLHrvzRPu2zbsGrvw2fVmPxX19yk+84vn4t8nE8hDhbGjTx1wR9MAxS/JEAFaic8eQwd+F9xeJ+hsoQ3HExLLWbm1Q86OFFHGeQx0gknNlRTE4mL+2qnhyaFn+lCdj71M9dW7dECEKVdpiEPskktgY2TN67f+zafiT7LtquSFD0k8kuNiP+5r38ePh2cJj7u/uLOs7dphBtTDrZXIYXV5AxYNxYvJmUsq9B/Om4niduC381B1410tHbWfgt1p8kO9oalPjT+Db4+GdnFWPjfaxExtgQB8m4VN060B/m/f7RIkbiwqLE2P7TL4Vvlww+HvA1dhJ7OlEhcS8p2i/ct4ivi9V3FlL5CQGXwscv/rlAiy2+zJy8IPwGK2gjGOPJc7saT47S+aExL49b+yX7ucV/eSn81Ry6HriiWKzpa3oykfRlScgCPhjRm4I+tF/z6SAgyA2yifgr9T8FJ2eTZx7rfVeFhX9SPjhTc/hsjR19Tudns33muFLbKYZL/FX5svuuqX3ij/mK8GAMxf7ntXyrvs97pT4f4nsf/wjJmCeq7NdnZbu65l9elGduIE7U/wY77gh2ZObPksSNb5P5Sl0hr3ibVV/T60fSv6USu5xURXFZ9p9+T+Fjd85x/cZuGX4duPHrRRwz5uQ+P0eKfi8TmvhrggSCBimHrPiLCUSiquPn3wpH1oMHP3yZEzd3bedLoNQSW1+7k3/9w3B0PXp+eatE3Idd21EfLy75nquJGXeuCCZNphyaE3+Ni1TvwruKZEUZkgxCKtqaThKxYfL+5EdFHxGPqUAVmxF/7Td/znUuON913n+O67ynu2Gx7Hlghuu84RTXOf2HrvOW01znzNNd55wzXPu5exf31cSFgwmniV2G7xc8T2OQJk+xvIM07/lHwm99WPDHJ13vk3d7Hy14cVH4tB5+EaP/+JtxSsWH2hmy+FN//T2f0cfskMT6NT5cBslh8esvert7n7jLzf3tfLf4zy+Gb/rQdZ8SNfdSsjDIhvL9eOzaRB903nZGjT0Pz3ILX3k2HNWHl/+mExcW9LhYhZ0ELgl1/vo8v8vQ8/iccHSBxa/+oRhj2KtxvlXjPOt0N/mm7xa73pxAUR+CUotJg/gjfvHPWVpEOBEoxXx/wo+xwz+RuT4BXiQ9edZxxaIW7EgXtdy4USYFC8S8Fx5xvYvudnOfvt/7qgzKIBprQp+4GMoiovioWjxpa8FLi2p9r4oRsPh1LaJX7l+9uOn3FLw/Lu0/v8e+z3vuEf83vvbjS7xEoRRzXCnvVJLjNAZVGC7xV4XOG08pTtrL4k/xOOC81lh3PTYlfNuHjiu+2ncCRH3Edoy7xC527FP4uYh/T1J+Jk+GE9QGOzSfq+ZPed4wrpx4d96uPCD7YTmWGeMiH8pe8mFystr0+hH6xxqZjV3NJfJxc7H7omvvSWI3PakKTJHGbcTLf3/NzX3mgRC/D2eP8etAKtSXZCd7abKlxV/i/GVKf09GP+LvmxJ/RymBcA8fCQQhR4ByX4POghe/kV9Y/IMfLPBnKbDZNWAh9IFdtFu1jd1+vIKGBz0QcUxKkghn3P6sRWUVUDnUiT/Kcc8Jiwdn6rGvar88AXsfu7Mo8/14D5oCl/swmIDB1siGycsDGYi5aCeTnYCXb5oRf8VCqrbwjwQar/1IgSBo+7qEMGPAJXBEE/fKIYpPUmJDPNFP6tGkLsPf/wjZPSWxcb9mGLuyiEix4A+LiqRLW5THP2q746Ivu8WvNSaZ7vuvLyY+AjAdK7XV+UhG/B2t+qiX2IgPBeFv+a7BxzefWoyNH1P5mGPDmOZ21Uh2k6cdXcSsp/zGAqg2O2ec5neWI0icXkQjAPGhYpRky6WPrl9eWdyb2aW2iWN8j838Do/bxHXf2/h+yq47Li7mSi0JyhfEPicVsp8djxQ+brlXFXKPK7bSDn1mYaDf8WEf+ZZ7clL0Pq745VgWXNr0Z/gh5jUG3NtXBgKk/TR9T1vEFX4Ksdl+qubmsw+FI/vA4uL9EYWZF/kaM9rRz/K4pfA2yl++X/gRajxy7fQsmFnMD8baL57FfIpzcDBs/9nB2VsBeh6eXcQg/U/iA1bFOIu8j1d2drlRP7VLP6tAXdRZm0ehHfzsY4txYwc/nQelvFPJMMeq4MVfLnc3W3+ZKtff7nhN/CG6auJP7clX/c5rjg1zpPwO2Z5f3eraTtA8INddoTzJfIqiIrGrvJ7MfWp+n8+JJ8ZN8dRgh3JC4/zZrWFzAuHXfrZOumMOh9Qd8gG5gNwy+XrlHvrPWoK9rEHB3qbXD41RZew+NKtoN85bH7tiP/m5LnbjRoyPs4JVQOT5fIYfk/htP3WPrNicfIP6TqzRF38JOLaTjNVIsbXFn5zSCvSD04+g8glEgcbOmL88oQC9lQAt2L2oNxxdD//gB+V+qIlQO2tTMKhM+x35BDLvdwuK9g4Tf6AJ6Se8kpY/i1BZ7NXPHArxJ6H0vTCZaPNGTWR/CTf0NXPvSe9jd2jiqAyL04+1uHHvBzsb8on3TSwrZidv7COJY6oSOHbqzKrz0cxTnTFpnB58yfGcaeIb9ZMt9xTs+LUdIlFAG/iDdjhD5UyRHdFL1cerZS9njLnLvvQLsnvkx47kr37Jvirx50U7NuIP2jxRQvOUIEJO3cK1n79Pw5mfFwbc43m27GIXbZra4ewSPzxS9gPiT/VzSZ++pP6W7xp83CsfYItfUORjjg1jyg3dKbCr/UxNfJ+k1Mb3Vc7br7LEb7A/7mKyg9d2svqGL7Gb2CbWGBfO3OkPPo9k3NipQehiu/zKjk6KuU/eV4jzH7HgqA58wYKC3epr5y+6w5EF/Dwh5iFjhR+xlVj0l6MkDK4MC7fiuUH8cfKCf9jh4FhiAWEm/5RjEPidQo7HP8fKT4wxZeUb3y5UX3M7wV7k03/mVvQVcyQzboDx8ONH/DLeiJ00njQu7Bik8PGBD+j/5YrZ8hweBHMx3jlbc5Z+xxhnrIiB2Hex/bx9/ElEGR1X6YQIu5hLjKs/yVFbFTkJMdB+onwU+x99HeOROGKMqY/7/sgFPh/X96OSHKf5XIXK3N1s/WWqXC6mInyu+rbEH3Ml5nzyQDPzGn8qdsu3Ei1+7Q/FPKYP1Bn9ntqlPpV3yLzgJg/QBnPVz6GM+LtFIrQ8fxTXvS+W5lmcN9+RP+PxxDBjyJwgx5IfmEe0xxUvcpvfSSzsHcz6kY1ddinJEV50iscrnvAfbfq2FbvKb9nYvVKxy7rBnCIOQjtVaz9XJDrO+1LR37q5q7Zkb/sFjeuAP8njOOZI3MkMbdSN10iwpcVfnOTLmpwJViSQhS8qER8aEgiBzpkDSYoBhSrXPus//OWxHDrOPkgJTwETt7WZCErkPc/lL9X5nS6EHwmEM7HyfRjYmxE5wIs/dsmYHOzmkChYcGOChqqjPAF7H5X4iwHORPbiReVIkv4suY8Nk3emzhpTW7lvg4VKZ2+Nokfij7M0SCILZ6LePs4ONVHKD4D4s2Muu5NsmNzxHj92CvELY0EfWYQzfmloL46d7CuLCNB999RiB4qzd3ZnWIQ5a2b86F9g+dIl6Ljg4L4kFv0gNvgBsRPFX9nfOr58M7kXwBzLAk37Pjnvlt2B6J5/XXHPEfFKgqQMJxBc9iYesI2krOTc8+js4vK5Fxo6xotx+YcY5Sd/cyzfcdmIOjijxY+MAfGs37sfuSm0XsD3L4q4eMsC/eNsW7bzQE0Kfzz+hogDfEI/qZ/FA1+GBYlYaRB/xC/+oT1s9Gf2OlbxuuDP9bt+/tIMvomkPeKK8cU39A8/0W/1uXxpdsHvF4bkruOJwZjcZVd53Lj1Y/IV3yriiTGJ8cRCiT/DWHTdf0Uo0Qc/diyu2IGAYExKc3FA6viyIPA7vfiZvhOD0Z547xl9h/Jjx7T/CaX60PPgzKIMxzMuzL0Qt2XU9Z82YwzjO+ZxjCXGmRiJuWow/eRY+b8Klbl7sL6MVF97nvtpqL0eL//11eKKDTtS/lUv6p8/4c/HR3Zea57wBGwZXsiltwDF2wGCXV0Lp4YjC/iT0ZjDiHHijfFS/Q05/OZgRzp/FG8Nt1cgbIgZ/MmxjCN2kwvIFfiXmMZGPieOaDOsedg5mPWjIXZ/o9ilfeYS8wMbEJzYTLv4m5hSPR3Xfy2U6oPfQWVOxRPdsGYwpmUguNuPkZ8ZT966QXtchaA9yjMv1ebcxQ+EEgV8LmP807WbNoi5GEMjRRN/TZBJlAkA0K/4I+lRVkFUvlE3Yu4T9xaBUztrK4RKbjvbP+jxPxJvBBuTlkDzlyrDAhMneybRguVS/JEcOR4b5ZeFfymJPy5JMNlJfCQbLqtShkRJ30gslA1tljEY8Td30X2F7xGbXjipT7SJH1mg6Ftg+3WfCaX60HX7RYWdqdCXbcMj/nZ1XYvqEz5nod5ukj6XYrCfpM+ZLm2waGA/CYlkTV0kMvpI0kRoUTf+xB78zGdRbPM7dXA5g5iE+jsr5ugfgp26Y72MkXzS+eD54cgCtYQJSc4k8xj32MFCh3CkvNi0+FPsluHFcbooInzoexxf+ke/8dGVO7iehY0PAPm+kQsoRxnskn3lceN+1WIXX/GEfewYEBssUuzCUFa+ab/hs6FEH3wbiEyOxxYvsjQHS/Oxkjout0PVcelX+oQYixmXwrw9YWxj/8O4L3j5yVCygN+VpCy5iRhiPgVxU0Zf/8XYf+KRcjEeaYvxinmKunL9qSL+0HyuwnCIP15bk8OC557oa6+Wb9Q32lPfmprX7PIqdsu3Es19cn4xp8kXxCrH+n4U/ipfAfCXRhln5iB+RxzhZ82lZsVf99O3hCMKcDmVy50+NjnJRQAxTxnDSGKasSVm+Z35y/zAVtnZ7PpRvvcYdFwoAUzbkDzB3Ih5i3K0T0zRtny/4OWnQskCPs9weZvYJeaxjbySiZ/JVx9Z3EKFD8mpMXZZC5L+8YR+Ct9GXK+wj3lOLhpsXC8Nmvhrgj6pLqH4o7yClRvac/APfsQzpXDWlrupF/Q8oDMTxBuLILuFBFst8dNesFft5bBcir+SkG5IkLX6NdlJNvgjLhLRvjB+uUk8GPHn/cBkh4xXXKhC0vT9itRn5QTt3/FFgqat6HtN/OESf+Uz8wW/X1TEWmo/yTnY4X0W7eczkiVt00cSKAsV/YzHkRgRsF58ifidz4P/PPVZ50MZMUc8xRMYFit8GMoNGBdxxyS2VRtjUX83Jf4QmRnx4/2OwI87ySwesd+0l/SLOjpu/2Yo2Qc/HiR3/BuTu45tGDfu/zpCbUVRy/yPCzd+jT5W22X4S3Gp/yiTmY+V1HHl+Cj8LFtYnBC+XJpjTkR7Yt8hdilGun8zPZTug4+vuCvJfAz9KMPnTXxdjkdiPfY/tufHGWb60h9DTFRhqYs/lc09gAB67rul78SRe4yJjSjSFE9Nzevgl56nfxKOKuA3BuhHzOuIHPynunNXANrPmFT4Pe6kM8f9PJYdzYg/Hds+96CGviIAJ1/7nSIu8Sd2ECsxN/CTvyP5LBnXZteP8hz3DwcRS+QI5i6xy7xgPGPbxBE/oXzZ/UTj7Vi1KxL0kxyDTzLx423iEj75gpMkYpdciW+S/vIQWxn+hAcbo49ibinH0nCzpcWfD4oWIJNzRoWgevF3SiAKgiMVDJzt+IVJARrvF6A8v/c2nq1FdP/8GiUEBRG7DJfrjCTz7iBEYvv3FVjcs+fFm9ryZ2sK0JuULGNbUIGXQ038EbCUj/eRsDjFsrI1K/5ILNHGWtJK+hjYkMBuDZO3thhogsSJ0bDIyz7a8cm47EuxmfoRKfJ1zf/RPsrrszIq25N9WRHBOOM/FouL5T/6w9l4bDNSC2P5EvW83z1UjF20lbFT2Yb/aBHFUc7faie7SLCgUC/35Pjk3Hj5xt/7Rl+pO8YP9jP+JJ/gI08+QwDSLj7hZ+xnPI4y/M2CRAyKk+efVDyd/eB5xdO7vzpXC9XcYEEB3z/8iB1edCOw5IvQdlNxwb0/tE+ZJP74Oztu+If7fxBYtKW+lC/P+UthtIEgi2fm7IrWxHFoj/7HvquuMjpvkqiLyR1bKU88lMeN4/ADtp0R/BDvcY3xRDtquwy/IKf+Y6HytiW+6I86tnzJ29+LSf/9ZakQoyxojG0c98hgV+cv63d1gV+EERX+vib5j/Lydxl+EWTuMieiqGdxT/sf/Z3O5cGQMqqjCgPm7kGy64n63fYUHWd8vogtYgPfkKvIv/RPgqGpeY0vZV/7jM+Fo/rgd6O8iA47SmHcyjt0PKzmfU6/qZs50aPjiXEdnxV/mfmDHb3P5d9RiRjrXnBDIUQZU8owDygX2vHrQMnXzeZ3XqCcwj+8wg5y9Nd5spN28S9t+HbCTyg7On+diV3mVDo+5D0dX4b3XSriWEujX2JeEstXMYAvh5gml8U1GH8kcTQiNPHXBH3iGYL4C8my53f1Z2sRXpRRXgmXd8LlMO/pBUU7BE6XAo4zG87WmFDlwHlTir9B1k+ZxC5fXp+VUdme7MuKCHzHhPeX25LkXfIDY9L7Qv1/J6mJOhZG7omiLZUfMfEXx5HEw8MW/Yyj/5vP8UUYr3QcYPtPDvILCyKi2ZdHA98/xiznd3FJ4qJGfdas+GvYPYiiFHIZh/kRd6rxRdoOpG0tsOX/4+p3eGkvXk7DxxrnhnFD/BFPMR4QfiweaZ/4XX0qwy/IMedgZxTDOTtzVJ2V8YEwYEEr3/herkOfcT9zGb5f3GzPziljFRb9MnwuI865fI1g6W8+LSkr/BextMVf2acRPBzQ9j8fKtpCoBGHtBXHW3OsqXmNMOZ4+bS8SeDfHcuDH/GkA1/q+LLI77732iLuYG0nPcSPOBjxR3zwsuQq8MqVuc//sngROico2MR6E2O15OcB83sQf+Xbf/z9hoi/KMY4IcqtjZGyvf22L4TSffB99fEvvxD/9FW2luHnCUKeBzy8eJZd9AufJO2Ur3oAH/fkdk6wYn5I1+CRoom/JkiAKlBzaE78FeXbZ34+lGrE5Cu/7ZPg3GfrbxCNmHzZEUXQMBH8ZYAodBoDzsSfji/7hPL6rIzK9mRfVkSQGFisztFilVusIylfJf5I0IjHcGY6LOJPia9hHBEl1BvPbGuLbcZ+yOe06f0P42fFTe1Vl7cGgo9DEmfO7+KIiD/5p1L84aNmd9Q0dxoWIvxMnKTjIT83jBsiieP8ZaZgF7s1af20q/bL8IsUcR9F6mDFn46tjA+EGyeX6c5UVf8zos73q7yzIX+X4Rdr+s8ua1kM5dpaElb4L2Jpir9y3KbovnNKcsuN2iov+oMRfxyvn+W3SPhLv/EyMblQ8VRec97gvl/mEXaQBxjnmF/odyYuKsUfcYHAUh7r/PmPG55KL2PeHx517dfxQmXFVayD9QtfB38PmN+rxB9XNdIdZ4Qbc4k5EcanjvRV9ZTh+1o3/xUPmfXUHxNvb+hnLR5Q/FHWxF9G/Pmk0wJkQG9pDBTgxV/t8X0NJpcCfSIOgZDWceNEN+/lx0LJerCz137q7g2PhgP/KD9njYeHZMkZdQxM3w4TKGlLgZSDX3Sph8DlVRIXEnhhwYllVV92USBB0vaZaptLOX5HoNRHseGBDCbvt8IZEgvcVUo0BLomSufDpXvB/CKvdiAJMuPLpuunTGKXL6/PyqhsT/blRYR8QII5V+LNL1aauGk7kaqj9/cZ8UdbJOizJOq41CI/Zu+Jiwm67O/pXD4s+YDFFrvwwfkhOU/buTFBxsWdnWN2WqYqYd1QYX8V5cfyzeODhY9DEqBfdEtzRlySuKjR+72JcZMgqRR/R8tHzLHLNceu1bGZOK9R41He+fNPhFPHCWrPizrVoXnW1LilcxFWxK1fpIh7v3ugeTwlLj5iWr6KOrYyPjg5OVsLKHUSH1V9F9vnNO78dXR/sYjdk9UvL1qKeCyjuEw3QP+Hygr/RTSVu5tg++1fqNz99rfsHKu+ITSP09yPrzjCt+Qq6tDPQcUH5VS+/BaJrp9eVIyfv2y5g+teWC8QeQGxP/GiXuKT+RDzQPBVg/jjlTPl+UPe43js0dh6saWc0jn3DDdv8UPZdQzwMuSO6V8v5hb10G7i7wYflPM7OTOTA/3ryFgfEaicmCNodZyvO4xRHTVPcjt/Hed/KZxUKR78zr98o3rK8Pn52wPPv6z4Iw6+q/LDGffN0MRfEyQwNag5NC3+oIKIe6FyIEHwnzty8P8SCNFGGz8IC3fctSm34dsx8dcw6Smvz8qobG8piL/yWaz3I235nZVhFn8ZsdH7yM+GLP56Fje+xoKE3rvoLv9+uPazJhWLD6Qdkc9T+Dhk4W9l8Zde9snEeY2ZhcE/yLFcir9SfETxlysfWL24qV9xZ+PNLv50bH8nRP5BD+7VZmcqXvINIsa3RR2DFX+U0+/z/li/mcBLwb3vwwYB/0s3xeTrv1PEDbt+fmc2jE9Sb9Pij+OJOcriN+YL8a65wyuieHI+919qeMee33FEXJGviTFytupr8EFO/Km9htiN4o85h/gr+7dMzZNyngE+FsgBJv6WsfhjArYC2TpWEOVQJ/5qAaOJQCBQLq2HAL9xl4Y3tPcHf9Z4nIIjPuhBGyRUf9akgEnrj7ypH/H3tSD+0sTM9nssK7vLr6WpE39190I09jE7eTnTJNBj0uPShXzRsMjHxdeLAhJToy+brt9PxMQ2yuuzMirbk31ZEYEPSILxsm88Yy5Tdbz8j9Kb+Hm1BW35nT8lP2yVH/sVf2V/ZxKfXyQ4Nl4+5FKlxrU8jguef6Kot3bZWQkrnkA0yfLuBi869k8OElMk6Wg3ffQCcNO8+Iu3MJTnjLgkcVGjPmtq3K6f6Lp+0/hUvbcp7vxxTy2+zMR5ZMddmXeu/fiLhT/Se7s0Hk2NWzoXYUXc+gWZuE8vO5FfsDUtX0UdW35ZsB+XQcZH91M3h9IF/KVH8iH9ipfqiF2J3zJ8DAzU/6Gywn8R/h2DzeTuHEPdVa/xAv5ev//+t75L3PEeO9pJx0s5a1DxEdouP3DDjpvvz0mb+R22FP7fuVEfccNcqN03HsQX9arOhkuvxBrlcnkPO+gDdrGRwGVZ+sfJA32V7b2/uTPU1Ieuuy4p5hiXv/1apvpU14D5nR09tTX3D/X3GfocgY/TnT8EFWOJnWXK5u7fZmIX38V4iA/EqZ4y/Dwh3w0w/3j4rQw/P/zJ4TDGfTM08dcEQ4DnMCjxR2AoQKqekMph3m8XFMKPswWSMhOWSwYkZUROWn/kEMVfefGc94zOJll46xbFfB8bJq9/D18yeZdj8eff84cP4uIYd1/L4yzmRIFP5uniSnn5f1jEn8RNzzP1Dxj51wrR13hPF74iYWfsr5HvaFc+mfxA4+uK/E4fdRJT7A6QfNlR4KZrLj2pn513Zf5dG2NGufTBCvwujpT467i7cYy65l5U+D7eW8ixuXYCe57NvHIj7nxpAa6JnxYUf91P1i9+oP1kfYdw5/UfLKDkh37io/zUpd95ov/UwVj5e9uKeCxjuRZ/+r7j50c0XPJPwXybfMkRRc6lDeKPeY9A8vMuaWdJxB/lNT7lzYSu2y/0u7flF80jwvz93swj8j+x6fOl6qTP1KufgxJ/0RZiD9uIF3zI1Qr8yfFnbun/R3QK/4CG90caZxkfVIi/8uVs0P4Dtc+udU7Ulql+LvhzKXZZ5xindP7Tl8x6auJvydGk+MORLUA/SRvVPyjEn8QZW8A+gSgQ/BawBtMHQqkefd7x08Z3g1XBvx6A+n2gKVjYJu5RYLPtThtp/ZGZMxVQiD+dhX6Hya+6LlBd1ym4/f0boaz6Wb5XzS9oR6p9yp2mSXGpJjWXDEt9LJ9Jgc5bWKSU5OP9JdhOspnOK076W+TzvmxMDqfW139lqL/sm+D7Mirbk31lP4Duefw/ZsQTl23VFv6Tz8pjXd4NeIMzchZFRJK/cZokqramVYk/2cSlAS/+lIS4dEg7N/HgQG6RIJmo3vNUL8Jci8vk+SeGI/rg/zVdrt6S/bDriSl+gfOXTxiv3CUMYuKbIZnRLy5TcxnkMtXNJR2x84FzwtEFfP+YLzm/i0sSFzXqs/K4FeJP9nHLhF+8Cr/Tp/LCWbON+UE/rlYf6D8+StsRi/u86sv716Uwzghh8kGcYxqPpsYtnYuwIm4L8ae4JyfQRj92Zqk6O+48PNTWh5qvTtc8ZwyxqSI+cicDXT+ReCYe/NO+LKDKFfg6d9mX4wbq/1BZ4b+Itm+E3JqOd8hPPr5S8pnmH37rb7cvovuOKUX9h6mf3OvHnCN2mXP0M/Wp2hx0fFBefi3vgvl/Aar4K/8Ls44Lwr8ii+Oby+P6vVH8BTvS+ePFXyiT2hP9xPfEPf5UHPU+/fNQWwEfZ+S4UzVHLu6bz5X5/UT5oJbfNQaZNdTfthDjjkv4CGwd22CnOPmBk0KpPnTdJtHM3K+Lf9ml/pThbY9rcj/zr3NB5j1/rOde/A1j3DfDlhZ/BFMrkLMiBWYOXvzVEogC2SeQImCKM8gS+UwTdsGr9fdi5ODr/uq/FosJweKFlwKSyVdVPxxI/BG4UUiSiPyWeyirfuYW+a65YWJE0cgZI+VCoiw/2RrhF6m67fggzsSs6OHMK56JZ3xZTg5+seVeDxITO01MWL8rSplIlaUOsYzK9lQ+J/5A9y8koPzCruM5E2VxY/KGNibf35hY/I5I7XJY8D2TXmWzfkDoMOZ+pzUswvRF7WQXiZhM4j05JD4du/iNl8JRBRDyfneHccQGxiOOI/WHPsTFrff5XxSJWWf7vLOvDF+X3+lRvxBmMUHjR8VW+y0HNrzf0vePs/l4wpT6XczFX/vJGsO6EyD5HZ/XxpnYLcY5K/7wT3ovG/7h2MWNu/DdP59aHEs8Md/YlcBHwT7fntrNCQB/wzg7WnGxj4tQlfgrj1s6F/18LPpURk38sSOCPxDa0Rdp+SrSDx1ffhclJymTr/524Wd2WtjBYT7ha+/ngjzoUd71ql02K89H+lQl/gbq/1BZ4b8If1XF76AmcYUNIbboJ/HY9fjV/jJ5fzt9Kbzw+y/lWuYG+Za1gV2eON/wf2onY7Ek8aG/y0LIj+HUI8NfBYp/56Z+Up+/gqSTV2wh//sxDfXJrqz4K88fcl7wrY87GOdj/J24oX4dz+teUvh/pVZbTzT//b3aGR/MSE7u4/pB3ZqTDbHLTus1RxXHYid1MnexEdJP/Wy/rSJ2iUfGirmb+kdlyvD5OY2bivmXu8ffiz9/W8gwxn0zNPHXBAlyDWoOgxZ/UMHb9ejVoYZqdP/s6uJ+EeqOixHJiYBOJ2yZCsIcmhN/omwvP0VGQvFJABHHxCKpa0HjLLicLFJ0TlcZFsOlJP7K9ylhl9/uJ6HxFN0l2/oXoLbP+nzRDmUjM35ZEvEH5v52vmu/5FPhJvEgJuiTzvRyr0DpOO+gQvwhkhDx7AAEUTFs4k/2dD/R+B8YeHp88g1H1/zlYyAIZmxJE2Pvs/cUfWSXULFXhr9UQtKMC0oilqirvDMG6sRfec6IJOcyvICjjL/8oz5KlHTccXjfgkPZkNwHI/7abz4w+3+3uSzVfv7exRzBNvpEOyKX9MuXO4G/6Zw+sVgR71zS4pI980v+bSnxF+ot78oCFtHu+67t26lK4gmWYyTC20SuwgfkF8QO+Ypy6lcZrSD+ljbwXdfM8/tu1WEXiTEiFhDS9DE3TvpsieKDuhRbi/9af5LHHE/hT1jjAzZxbPwOuOoLudVTvmpK/CkemNsci8DxYpAYwT5sgqqLn5PvO7Fhjk2ecmRf/CZx0pT4833WSXPmZJT1wL/HkLxJbmPuYlPIE5Wxy3/MSccLfyd5ogwTf0uO5sQfQdkK5Fp+RQLx4q929qiFzJ/FKGgIBMrl6vPBO7HfBz/8/VlflVCLT+f6ezSYsAoUJmxV3fDGClsRf4hJAjcmAAIvJgBIvbKv6r5EziB5srP3tz93C15p3L1c/Jf6JOSffET8xftFSIDc3yBmRU8UY/Q348uuxxpFM77if1v2LrzLLfjjkz7R8OJRn1CYwPQxJKYyKtuTfVW7mREkGtrrffoe1/vMPQ27bBE14QLxQ9wR4f1Osql8X0jND4w7N0373V71gWSq4xsSZHy6NApsjo2LtX5f+Of64yO4LNT71N2u93f3yF+/zNrf85s5/p4dvwskO+a9+Gj4pg/EFf/Qn9c8dN59lut56vaGs/IUPg5ZiOIJU+r3wNx/w8Ev3Lc095n7a3HG/731Zf0Yy5+K5fK4+QeW8E/pXkvvz2t3dl0L6v//ZoQf35cW+UtWjC+7hFX98jsrjK8X7eyCSuAjalkUiHfZ1dS4pXMxmY9leKHFDlu6eNIOfUrLV5F6OVZ+q3pJLw8IzHvhER8f9H/u739VGeP+PyxgDyeW3O+HcPT3TIVxVb/KqF3R6K//Q2WF/4YDrAX+Nh1yLH0jFrivK+4gc+8n/Qu5rI4auyWKD3yrnJD7N3sp2o/Xccw5drUQRtyPhz2IjlJ9DeKPE/jy/FHZFKxl7O51PXil65x/tuu8/xx/4ll+Ghk05Pnk3sOs+COuog/i+oEfNIfLO4oRtdhl7uoEtt/Y5epRFHP00Z/0BP/QTiZ+vO0cP8D8y4o/Nou4Z3A4474Ztrb4w5EtQAZ0emPyAn3iTwGKoOKSqD8L0GD6QMiQ73QmQkBWYe7j84pdOs4SmLDcS8WZTLxHL1dvpL7PYeFLspXEFHf+/P0Gmsh+Cz+UDX3l86rJUoWeR2c3PNnZecPJxRm+v1+Es18lQewXOx+qnxhFUtCEql0OyPhStlb9m7wUC19bXJTHZ5wtht25Mirbk31lETF34b3+fYyDQXG5N8QHfveXi0kWJLHgh9J9ITU/lO+xZFxuyFw+rC0S+JhkUvTV+0zx0n7TZxtEeTNAHLZ371mc8Z8hO2R3+9TJ2Z2y/kDb6f1HXvyxOHrxV/K7H+uJruuRq8LR/YOXy3qRxc4k/b52p37En+YROzDcn3O95hH+IfZVrvuRG8PRgwevovGXpekTY+Z36SWYiXV/z9Agxi2di3E+yidl+N0YL/60gDCPYzzRVlq+P1I3fpA/eAHvksIvnowl89zvnLCoyc+MKfmKdtT/MvrEXz/9Hyor/Lc0wRO9XbPZ7dOJOn1irrPDT44lDpi/xBx9Y4xydurzocRHe++BoVQj/H+HIgd5EaW6/I60YpO6mG9pffq7wY6a+Evmj+J6ScBJUvuJaof8Rj6M9/BSZ67tOvGXrB+KJ0/l9iHF7lOKXe7JJH6xh3zEfPK3O4Tx0pwqw9vvdy77n3+dD2b+hZwXf2prOOO+GZr4a4JMsEwAgCUSf6G+jp8cGmppRMepn3NtX1cySQMMEUOAlSdsmTomhwbxx05iWfxB7NOi0D79s27By0+G0tXgLKtzzul+0eMfcafwly6YvHHb3p+5yX4xK/44A4O1y7AlX2rCT/7FCQMKEHYn/c3EJCuSS3g4o4zK9mRfo4j4mU+ivQ/9LHxSDXaNen4d7mthDL+n5IkP/OWfIApoR8yKP8YovfGYBEFiyYkIfMyx8TJCmkz4qbbar5ns5j57fyjRP7C99wn571gtYCR8hPuPwsmHbOmYfUjTYnLu7+537Wfv6f/XZ0Rt54+HiE5RHKZ+j2OtscrtGpThFw/O1InlIPIbxo2dV/zjL1vJ/1PUFuIY/xCL/K7FcPJtxw34XwpS+DF+cGYRP4xXTOjYQ58YhyjCBztukZSVT8qoXfaN83hJxB9kAeWyvwRK1/zLsu9lq4Kf99yQzzjSdwQCuQrBE28noH7akW1l+EV3oP4PlcF/gz1hGQgv//VV/yaGzutPKk7SWQPSe8bIPfSJuetvqyAOQmzn7JR/ljg+oNoov9Mvwl+GjrbFk8+rKtYS/d1gR3zgI50/yin8h5HB+JX/Kdx+2u5FTvTvDVR9pZOkhrbTB/pK64e3HZ/Ix0scu/gEexDrtIE9Md/GNmRXGb4cgnGA+ZcVf/GkZzjjvhm2kPijYQzAEAyaWAvsZU221kUe0kiDnZtE/b/tQdxwiY4JH89ifOCU6knJd5qw7P69/Pe+y7/+EuYT9xaXe71oUFDGp5eaqRfeUPwnkTpblaz8fx7gDJA6WTS53OYv+5KYGuvwSUtJvPPOH/k3w9PfCOxc8MLC4ulRJg/b4FoEJ089yi+K/hj99DePM0n8bkCYvNQt8jRqamPxj+VVT0xSLKAI6bTPlL1uZ/9vgrj0nIoKgHBisW8/ZTclLPWTMzkEF2ff6mt6qd3f5FvVntrJij8mrnzYcc5B3t7yvTW03/PLGcVllrgLgDjgzJV77IgPJjuigD6prfI9Mf6VMtiE/fGeP8qQiDRW6X+J8T7ukY/9KyFCMknuVfF9YXxJThrvjmv+y186xU7GMAJfxPGsPVwBiRVs534+7KAe6lc/uu67rCEuAHXjm44LD675l78j/NOIR6junN/pI37BfrXDzh6XXtM2iGVs9QKIRYlLNeyMM0dUT/nfXhVPOKsfcfFiHsXLvmEM4iJCrHTefoa/jEk/ymC8uc/R18nYMveh3xlR/YwX8wohSh+oO8TtoMYtMtiXPiCGLzrOP6hx8WFu+MUqKT8QsY9y+ATBphjl5bzsWJdjG/ixVXzWLjtD/EA/YoxTD/VRb9L/9P5PFl9/AjBQ/4fK4L+uh3v6vc2mP3CyAsnL3XdNcZMvP6KY2wgq+k/+i3HIZUx8wJiwu0afmH9+bEq2pdT3SxQfkfp88s+Pr1tLgD/R4oQfOxE4nJik+aRsk3yVPshUy+Hl+UN5ripcd4DrXjDN5wF2wFNQls98LuBBKOI1rhXUxVUNhCj9CvfUznu51Pa1R+XXD+IK2/EH5cmrxO79TcYuMUv8YU+8/y7m5+hn6vesv0Wrtm5QdoD51z7zc3Vxv/DlZ/t2yIcz7pthi4i/VcTWFX+QIEAokdS5h4OzFhI+AUQgpJdmGczcxCqTpECdBByTkglBoMfAZOHlngJusu3RhEOMDVQnJAiZTNxngq0EGQKEYKV+2qE9Fkvq5PhyHUwu7GNR5jgWfwKdnSD6HUlSIKn4HSK1wzG8I4mfLAa0xXcsinGRj5MX4iuEGROPYyP5G/v5Pk70aBflo10cRzs84s8k9jaJ/M0Y0S6Tk6TBJSjKVbanz2N7aiN7+ZAkig/pMwkp9pHxZ7zwB+1D/uY7fIH/GGfGkYkefU6c0B4Jlf4wLnG3jfpJtsQccYIPKEf5IFS8eIpnrZwk4ONU0Mf6Y+ziC9rAJnzkbQ72Yjt/Ux/9wXZOEqLt2MgZOrFFXbSF32gbmykbSR3Uz+fUg5/oD7/7z/XT7yiW/B7HmX4yXiygJH1iKvq4Ns76PfoXX+AT6vFiV7ZiHz6hHDb6Ex71n4Wr5p/AuIgwf5lvLEzEM2XTMU39BKOfGAf6EoUf/qYPcTEY7LhFYht+wTbmQ4xb/EfbcR4zNqn/mmWsnzzA3GCc2f3AV3Gs0n5Hpv1nHBkfcg3lqYf6yuO5JP0fKmmfMYjiHv/hO3I2i3A4matmOCaSvBwFH3GIf4jtOE+IL2I23lfqY6BkU45D9Q/l8TlzifFj3WCORJHCOFEnYoPxYW7l7MJX1MUx/c0f2krnWcwDMWYi6UMkf/M9trFWpnmZNmkfH1A/7dAeddJ+9AF2cSyxxfH8jp+xw8du8B1zlzaJ0fKchdGeOHYxdqknjpv3R2DMn4wNNhHz5LaG+RfKRVIPvgonVr7vtN/suA4n0VgtJP7eKUbxt3OxTd4iZFAJUra8L1JgchnMB6eCgEtX/p4oRJoC5FoFL8f7QOiHXBLhnpsrNeEJduo8SUHBIkm9p6n+bgXMJQqQqWp3mo7N1VPmjaqXY9naj8mcHTDqhn7iyVbapX2OL9fh7dfnsc8klXMV+PSTOri81aXgZxJg6w+Z0PoOsUJfuD+DdvmMHVH+vkx1UBftQepHTGAHl7Xpb6S/zK3P+Z7joi9rdunzq5P+0QZ2YA924UPGJfoPX9BX2m+mPdmX3fkjkZJM8AHtMmZMYtrCJ7F9bMHn+JqE6wWO2vZJt9QffMH4eqEjP9EX6sR3F8qX9NOXC8cytj06Fj+fpfppO/oeH+MbYisdS/6mDvyAP2iHNrAxtbs8nviFOrEB/1EPNhDjfMY7us6WH6gLn1A21kO9J+sz+oOfOA57OTaycpz1O23hFy4LcVy0l7qjvfzN58Qzc496KIevsRuf0BfilvFiHLA99U/aXoxH/M7xxIYX+aG9yOin2Dfa935Su9FPsS9wScbN2wUTu6IfsCvOK+IGP6X+GwwpE+3Db9RHf+hXeV5F4g/8gh34iT4xTpSnHupbGv0fKr3/ROom9hlX5iRt+zhK+tQfY8zhi5hb6LuPa9lPn4gt+sdYMNfoC/3O2VXmUP1Deb6LOZ/yzMcYu9ga68nFf2SMhYHmTxzjGJfYHOMlN1/wG/ZQD3WSN7CVuqgnxgp28Rnt0B7H0360HbvS4/346m/mnM+hOoZ1mP5TjjbLscvffI6tMXbjHKKe8jzid8aTfEf8YFNu/qV2RfIZdcYcho/IWdEPwxX3zbAFxd+/iJuJO8lpfy0GtwWIqkedE5icARC8nLkw+PxkwsVFjMGOZwH9kWMYdMqwcHF2QIAgFiBnBZwJlheUgVhVb6wb2wnGuAMSgzZXD9/7wGdiqQz9pA4CF2HFmRC/s1jwHcGMf7CbdvkM/zCZazsCtBnqp26faHQ8kzCStvic7zkuZxdjEftHGW9TsItxob98F0WBL1PRHn+n7cl/WfHH/U2cuTHxKUcyYJxoK9c+/acv+I+6vb9LfcEf2MUx+A9/+bpVNt4PwxmxP14/GVvGju8YS9rBDnxcFSv8TdvU5dtRWcrU7JbNJELsT2M62o591AGxGXvwPwkcm6mrLi5Efucz+oKdHMdP7zORz6vGOfolxgfH5fzs54nqifHM8djobVM5fEJscgxtEws5/8T2+I56OI6ylMMftIl/Ivmbz2PfaB87o5+oq1w/nw923GLZ1A+0CRkjfErZ6D9YLt8Mo32xnWgj7QzUf+YYcz71f9mOWP+S9H+opO00X9A2vqMPMMZrluGYSOIt2k09jAdzIPbdz+9M/wfiUP0Ty8ecT3lsjWPHODVbD/YTx/3Nn5jH+B2bWfv4Po2X1I98hj1xjcBnPq+pvG8ztI9dfBb7QLu0jx3l9SO1GXti7GILMckY02bMFcRtHFM+T2OXcrXxS+qOJN9hL2ODTZRN51/OLkh/qDPOXfpP282O63CSDbZCa6G50F7riGixERd/NPwO8QPipuKOGsSns0YvK8aBJAgIRIKGYOBnGszNDiSBAilDWQKBwKVOSJ0xKKkzF5Q5Dliv/mbC8n0ziYrvaT/Wh03UiX3Uxe/UR3KNE4if/M3nHJ/6Jm0v+pRjOS6Sv/m8ype+j6EsbdGOtwnKLn7Ptdtse/qZFX/xEj9ncPiSdup8Avtpv9wPmPMvpE+1hBTsiseX+83P2FZ/Y5pry9stm0m40XbqwydVtvN36v+0rlgPjP2grjQmIkmaqd/LrLQXJvVHP0Vby2ViexyX60/aXrlfsT36FZnGPcdV+Skl3y3puFE3ZfEXZegTTOO2v7abZbn/0c6q/mM7x3F8f/bDofR/qIz+i+NJzmYxhpwIVTEeE8mcpyw+iPbH8R/qOAzVP3xH+xwb+xlJPXE+D7ae/uZPemyc27QX4yXmAT6jHurrL15ifdEHMJajjbTtMmPZ1IeUjTak9sQ+RVv6qxdia7neZuziM8qW/cPPWHag8RgOoq3YYCu01oiLP7iiOE6cIK4tvl18v7ixuH3bDzebkTV8WTIOJoMdAy3+vqSDmNZJfZFDqRMuzXo5NtZDwDIJUvJZrDsyHpt+V26zXO9Ax6ccjE2xnmbb0+/9ij/u72ERYBIPpv0q9mdXbqzSYwfTFt+V24r2IiyqbM/VGesp10U9VXXF4yLTNsr1xzZiO2kbKWM9qZ/KZSJjW/G4HGNZyBl/bCf2a7B+SpnalCufKwOjTeX+NFN2sCy31W//Q/vN2lCud7j6kCP1x3wY7RgsY1lvLyy1MVRGu5bUPxwT64hjNNR6KBsZy8c64u/psbHN/uZKlR1pfWm7zdo+kC05e5oZR29XUu9g7MrZ1GzZ4eJ5HfOlsXYQNwmai403NBhaDE2GNhsR8beyuJb4NvG94sfFbdu+/C8nFQPTYmTAatQgpn/njm+GdfVFhs9yxzfL4ar3zc5pO/l/bZaidtmXV6BwT0m8zJ8rbzQaW4+1fAiVC7l3bSDmcmdkrg2jsdWJtmpr2078hPg+Ee2FBhtR8TdWRPytKW4gbiT+u7i1OKntqu3/mDXeaBxOKulnxR8v8T0uiD9uzjbxZzQajcblhdfu+EZb+4TPSF9tI35MfI/4VhHxhxYbUfE3XlxDXE98l/hh8ZPirm1f/9B52Q4YjcNJib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</file>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>b={1:6:1};
A={2:8:1};
c={2:7:1};
TfractionA={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};</text>
</varsrandom>
<varsglobal><text>aNum=TfractionA[0];
aDen=TfractionA[1];
a=aNum/aDen;
A=A*c*aDen;
ans=A*a/c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360995  -->
  <question type="formulas">
    <name>
      <text>L61- N+v</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = \(\frac{{varNum}}{{varDen}}\)<br></h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<h3></h3><h3></h3><h3></h3><h3></h3><table>
    <tbody>
        <tr>
            <td><h3>{question}</h3></td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td><h3><br></h3></td>
            <td><h3><br></h3></td>
        </tr>
        <tr>
            <td><h3><span class="" style="color: rgb(255, 51, 102);"><h3><span class="" style="color: rgb(51, 51, 51);">{number} + </span>\(\frac{{varNum}}{{varDen}}\)<span style="font-size: 1.64062rem; color: rgb(73, 80, 87);">&nbsp;</span></h3></span></h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = \(\frac{{varNum}}{{varDen}}\)&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{whole}\(\frac{{num}}{{den}}\)</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Add</h3></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[variable={"a","b","c","d","f","m","n","p","s","r","t","x","y","z"};
number1={1:21:1};

TfractionA={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[varNum=TfractionA[0];
varDen=TfractionA[1];
number=number1;
ans=number+(varNum/varDen);
question=join("",number," + ",variable);
whole=number;
den=varDen;
num=varNum;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>3</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[whole,num,den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[(abs(_0+(_1/_2) - ans) < 0.01)*.6 + (gcd(_1,_2) == 1)*.4]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[{question}<br><table><tbody><tr><td rowspan="2"><p>{variable} = {_0}</p></td><td style="border-bottom:1px solid black">{_1}</td></tr><tr><td>{_2}</td></tr></tbody></table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360993  -->
  <question type="formulas">
    <name>
      <text>L61- N-v</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = \(\frac{{varNum}}{{varDen}}\)<br></h3>
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    <generalfeedback format="html">
      <text><![CDATA[<h3></h3><h3></h3><h3></h3><h3></h3><table>
    <tbody>
        <tr>
            <td><h3>{question}</h3></td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td><h3><br></h3></td>
            <td><h3><br></h3></td>
        </tr>
        <tr>
            <td><h3><span class="" style="color: rgb(255, 51, 102);"><h3><span class="" style="color: rgb(51, 51, 51);">{number} - </span>\(\frac{{varNum}}{{varDen}}\)<span style="font-size: 1.64062rem; color: rgb(73, 80, 87);">&nbsp;</span></h3></span></h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = \(\frac{{varNum}}{{varDen}}\)&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{whole}\(\frac{{num}}{{den}}\)</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Subtract</h3></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
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    <penalty>0.3333333</penalty>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text><![CDATA[variable={"a","b","c","d","f","m","n","p","s","r","t","x","y","z"};
number1={1:21:1};

TfractionA={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};]]></text>
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<varsglobal><text><![CDATA[varNum=TfractionA[0];
varDen=TfractionA[1];
number=number1;
ans=number-(varNum/varDen);
question=join("",number," - ",variable);
whole=number-1;
den=varDen;
num=varDen-varNum;]]></text>
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<answernumbering><text>abc</text>
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  <text>[whole,num,den]</text>
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  <text></text>
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  <text><![CDATA[(abs(_0+(_1/_2) - ans) < 0.01)*.6 + (gcd(_1,_2) == 1)*.4]]></text>
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<text><![CDATA[{question}<br><table><tbody><tr><td rowspan="2"><p>{variable} = {_0}</p></td><td style="border-bottom:1px solid black">{_1}</td></tr><tr><td>{_2}</td></tr></tbody></table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
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<text></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 360994  -->
  <question type="formulas">
    <name>
      <text>L61-L39- a + b(c+d)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<p style="text-align: left;">{a} + {b}(\(\frac{{cNum}}{{cDen}}\) + \(\frac{{dNum}}{{dDen}}\))</p>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                  defaultWidth   default width of the box
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                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
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    function newWidth() {
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        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
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        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr style="border-bottom:1px solid black">
            <td width="25%">
                <p>{a} + {b}(<span class="" style="color: rgb(255, 51, 102);">\(\frac{{cNum}}{{cDen}}\) + \(\frac{{dNum}}{{dDen}}\)</span>)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(255, 51, 102);">\(\frac{{cNum}}{{cDen}}\) + \(\frac{{dNum}}{{dDen}}\)</span></span></p>
                <p>The LCM of the fractions is :{cPdLCM}</p>
                <p>\(\frac{{cNumLCM}}{{cPdLCM}}\) +&nbsp;\(\frac{{dNumLCM}}{{cPdLCM}}\) =&nbsp; \(\frac{{cPdNumLCM}}{{cPdLCM}}\)</p>Reduce the fraction: The GCF of the numerator and denominator is {cdGCF}<br>The reduced fraction is <span class="" style="color: rgb(255, 51, 102);">\(\frac{{cdNum}}{{cdDen}}\)&nbsp;</span>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="99" height="28" role="presentation" class="img-fluid atto_image_button_text-bottom"></td>
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        <tr style="border-bottom:1px solid black">
            <td>
                <p>{a} + <span class="" style="color: rgb(51, 102, 255);">{b}(\(\frac{{cdNum}}{{cdDen}}\))</span></p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply {b}(\(\frac{{cdNum}}{{cdDen}}\))</span></p>
                <p><span>\(\frac{({b})({cdNum})}{cdDen}\)</span></p>
                <p>Cancel before multiplication&nbsp;<br>
                    (it will make the math easier.)&nbsp; &nbsp;{b}&nbsp;÷{cdDen} = {bDivcdDen}</p>
                <p><span>&nbsp;Multiply {bDivcdDen} times {cdNum} = {=b*(c+d)}</span></p>
                <p><span><br></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="102" height="28" role="presentation" class="img-fluid atto_image_button_text-bottom"></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></p>
            </td>
            <td></td>
            <td>
                <p>Add <span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="99" height="28" role="presentation" class="img-fluid atto_image_button_text-bottom"><br></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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      <text>Your answer is partially correct.</text>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>TfractionC={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
TfractionD={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
a={-11:11:1};
b={-11:11:1};
c={-11:11:1};
d={-11:11:1};</text>
</varsrandom>
<varsglobal><text>cNum=TfractionC[0];
cDen=TfractionC[1];
c=cNum/cDen;
dNum=TfractionD[0];
dDen=TfractionD[1];
d=dNum/dDen;
b=b*lcm(dDen,cDen);
ans = a + b*(c+d);
#least common denominator
cPdLCM=lcm(cDen,dDen);

#rewrite fractions with a common denominator
cNumLCM=cNum*(cPdLCM/cDen);
dNumLCM=dNum*(cPdLCM/dDen);

#add the numerators
cPdNumLCM=cNumLCM+dNumLCM;
#reduce the answer
cdGCF=gcd(cPdNumLCM,cPdLCM);
cdNum=cPdNumLCM/cdGCF;
cdDen= cPdLCM/cdGCF;

#mult by b
bcdNum=b*cdNum;
bDivcdDen=b/cdDen;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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  </question>

<!-- question: 360998  -->
  <question type="formulas">
    <name>
      <text>L61-L39- a + b(c+d)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<p style="text-align: left;">{a} + {b}(\(\frac{{cNum}}{{cDen}}\) + \(\frac{{dNum}}{{dDen}}\))</p>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr style="border-bottom:1px solid black">
            <td>
                <p>{a} + {b}(<span class="" style="color: rgb(255, 51, 102);">\(\frac{{cNum}}{{cDen}}\) + \(\frac{{dNum}}{{dDen}}\)</span>)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(255, 51, 102);">\(\frac{{cNum}}{{cDen}}\) + \(\frac{{dNum}}{{dDen}}\)</span></span></p>
                <p>The LCM of the fractions is :{cPdLCM}</p>
                <p>\(\frac{{cNumLCM}}{{cPdLCM}}\) +&nbsp;\(\frac{{dNumLCM}}{{cPdLCM}}\) =&nbsp; \(\frac{{cPdNumLCM}}{{cPdLCM}}\)</p>Reduce the fraction: The GCF of the numerator and denominator is {cdGCF}<br>The reduced fraction is <span class="" style="color: rgb(255, 51, 102);">\(\frac{{cdNum}}{{cdDen}}\)&nbsp;</span>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="99" height="28" role="presentation" class="img-fluid atto_image_button_text-bottom"></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td>
                <p>{a} + <span class="" style="color: rgb(51, 102, 255);">{b}(\(\frac{{cdNum}}{{cdDen}}\))</span></p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply {b}(\(\frac{{cdNum}}{{cdDen}}\))</span></p>
                <p><span>\(\frac{({b})({cdNum})}{cdDen}\)</span></p>
                <p>Cancel before multiplication&nbsp;<br>
                (it will make the math easier.)&nbsp; &nbsp;{b}&nbsp;÷{cdDen} = {bDivcdDen}</p>
                <p><span>&nbsp;Multiply {bDivcdDen} times {cdNum} = {=b*(c+d)}</span></p>
                <p><span><br></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="102" height="28" role="presentation" class="img-fluid atto_image_button_text-bottom"></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></p>
            </td>
            <td></td>
            <td>
                <p>Add <span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="99" height="28" role="presentation" class="img-fluid atto_image_button_text-bottom"><br></td>
        </tr>
        <tr style="border-bottom:1px solid black">
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
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</file>
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</file>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>TfractionC={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
TfractionD={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};
a={-11:11:1};
b={-11:11:1};
c={-11:11:1};
d={-11:11:1};</text>
</varsrandom>
<varsglobal><text>cNum=TfractionC[0];
cDen=TfractionC[1];
c=cNum/cDen;
dNum=TfractionD[0];
dDen=TfractionD[1];
d=dNum/dDen;
b=b*lcm(dDen,cDen);
ans = a + b*(c+d);
#least common denominator
cPdLCM=lcm(cDen,dDen);

#rewrite fractions with a common denominator
cNumLCM=cNum*(cPdLCM/cDen);
dNumLCM=dNum*(cPdLCM/dDen);

#add the numerators
cPdNumLCM=cNumLCM+dNumLCM;
#reduce the answer
cdGCF=gcd(cPdNumLCM,cPdLCM);
cdNum=cPdNumLCM/cdGCF;
cdDen= cPdLCM/cdGCF;

#mult by b
bcdNum=b*cdNum;
bDivcdDen=b/cdDen;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L62- Exponents and Square Root</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 361070  -->
  <question type="formulas">
    <name>
      <text>L62- alg expression- 3rd-5th root of number</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate {question}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What number used as a factor {exponent} times equals {=pow(base,exponent)}?</p><p dir="ltr" style="text-align: left;">{base}<sup>{exponent}</sup>={factors} = {=pow(base,exponent)}</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};</text>
</varsrandom>
<varsglobal><text><![CDATA[base=2;
exponent=4;
question=pick(exponent==2,join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>base</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361058  -->
  <question type="formulas">
    <name>
      <text>TL62- 1 raised to any power</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{base}<sup>{exponent}</sup></p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><span style="font-size: 0.9375rem;">{base}</span><sup>{exponent}</sup><span style="font-size: 0.9375rem;">={factors} = {=pow(base,exponent)}</span><br></p><p dir="ltr" style="text-align: left;"><strong>1 raised to <span class="" style="color: rgb(204, 51, 255);">any power</span> equals 1.</strong></p><p dir="ltr" style="text-align: left;"><strong><br></strong></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>exponent={2:10:1}</text>
</varsrandom>
<varsglobal><text><![CDATA[base=1;


factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>base</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361068  -->
  <question type="formulas">
    <name>
      <text>TL62- alg expression- 3rd-5th root of number (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(239, 69, 64);"><strong>10.&nbsp;</strong></span> Evaluate {question}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What number used as a factor {exponent} times equals {=pow(base,exponent)}?</p><p dir="ltr" style="text-align: left;">{base}<sup>{exponent}</sup>={factors} = {=pow(base,exponent)}</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};</text>
</varsrandom>
<varsglobal><text><![CDATA[base=pair[0];
exponent=pair[1];
question=pick(exponent==2,join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>base</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361064  -->
  <question type="formulas">
    <name>
      <text>TL62- alg expression- nth root of number</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate {question} if n={exponent}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What number used as a factor {exponent} times equals {=pow(base,exponent)}?</p><p dir="ltr" style="text-align: left;">{base}<sup>{exponent}</sup>={factors} = {=pow(base,exponent)}</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};</text>
</varsrandom>
<varsglobal><text><![CDATA[base=pair[0];
exponent=pair[1];
question=join("","\\( \\sqrt[n]{",pow(base,exponent),"} \\)");
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>base</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361065  -->
  <question type="formulas">
    <name>
      <text>TL62- alg expression-factor to nth power</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate {base}<sup>n</sup> if n={exponent}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{base}<sup>n&nbsp;</sup><span style="font-size: 0.9375rem;">={base}</span><sup>{exponent}</sup><span style="font-size: 0.9375rem;">={factors} = {=pow(base,exponent)}</span></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};</text>
</varsrandom>
<varsglobal><text><![CDATA[base=pair[0];
exponent=pair[1];

factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>pow(base,exponent)</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361063  -->
  <question type="formulas">
    <name>
      <text>TL62- Evaluate algebraic express sqr(x)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate if x ={numberSqu}:&nbsp; &nbsp; \( \sqrt{x} \)</p>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">&nbsp;\( \sqrt{x} \) = \( \sqrt{{numberSqu}} \) =&nbsp;{number}</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>number={2:12:1};</text>
</varsrandom>
<varsglobal><text>numberSqu=number*number;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361067  -->
  <question type="formulas">
    <name>
      <text>TL62- fraction-number to power</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate (\(\frac{{baseN}}{{baseD}}\))<sup>{exponent}</sup>&nbsp;</p><script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.0/jquery.min.js"></script>
<script>
    $(document).ready(function() {
        /* Adjust the width of the input box */
        $("input.formulas_number").css("width", "70px");
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><span style="font-size: 0.9375rem;">({fraction})</span><sup>{exponent}</sup><span style="font-size: 0.9375rem;">={factors} = \(\frac{{=pow(baseN,exponent)}}{{=pow(baseD,exponent)}}\)</span></p><p dir="ltr" style="text-align: left;"><span style="font-size: 0.9375rem;">Reduce the fraction:</span></p><p dir="ltr" style="text-align: left;"><span style="font-size: 0.9375rem;">\(\frac{{redN}}{{redD}}\)</span></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>Tfraction={[1,2],[1,3],[2,3],[1,4],[2,4],[3,4],[1,5],[2,5],[3,5],[1,6],[2,6],[3,6],[4,6],[5,6],[1,7],[2,7],[3,7],[4,7],[5,7],[6,7],[1,8],[2,8],[3,8],[4,8],[5,8],[6,8],[7,8],[1,10],[2,10],[3,10],[4,10],[5,10],[6,10],[7,10],[8,10],[9,10]};</text>
</varsrandom>
<varsglobal><text><![CDATA[baseN=Tfraction[0];
baseD=Tfraction[1];
exponent=2;
fraction=join("","\\(\\frac{",baseN,"}{",baseD,"}\\)");
factors=fraction;
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • \\(\\frac{",baseN,"}{",baseD,"}\\)"));
}
ansN=pow(baseN,exponent);
ansD=pow(baseD,exponent);
redN=ansN/(gcd(ansN,ansD));
redD=ansD/(gcd(ansN,ansD));
]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[redN,redD]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>((_0/_1 == redN/redD)*.6) + ((gcd(_0,_1)==1)*.4)</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table>
    <tbody>
        <tr>
            <td style="border-bottom:1px solid black">{_0}</td>
      </tr><tr><td>{_1}</td></tr>
    </tbody>
</table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361066  -->
  <question type="formulas">
    <name>
      <text>TL62- num exponent time vars</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{display}</p>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.0/jquery.min.js"></script>
<script>
    $(document).ready(function() {
        /* Adjust the width of the input box */
        $("input.formulas_number").css("width", "10px");
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table><tbody><tr><td>{display}</td><td></td><td><br>Given<br><br></td></tr><tr><td>{FB1}</td><td></td><td><br>Use the Commutative Property<br>of Multiplication to group factors.<br><br></td></tr><tr><td>{=pow(bN,eN)}{bV1}<sup>{eV1}</sup>{bV2}<sup>{eV2}</sup></td><td></td><td><br>Simplify the number by calculating the <br>product, then use exponents with <br>the variable factors<br><br></td></tr><tr><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td></tr></tbody></table>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text><![CDATA[pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};
varsAll=shuffle(["a","b","c","d","r","s","t","x","y","z"]);
eV1Pattern=shuffle([1,2,0,1,2,0,1,2,0]);
eV2Pattern=shuffle([1,2,0,1,2,0,1,2,0]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[pair=[2,6];
vars=sort([varsAll[0],varsAll[1]]);
bN=pair[0];
eN=pair[1];
bV1=vars[0];
eV1=eV1Pattern[0]+eV1Pattern[1];
bV2=vars[1];
eV2=eV2Pattern[0]+eV2Pattern[1];
display=join("",bN,"<sup>2</sup>" ,pick(eV1Pattern[0],"",join("",bV1),join("",bV1,bV1)), pick(eV2Pattern[0],"",join("",bV2),join("",bV2,bV2)), "·",pick(eN,"","","",join("",bN),join("",bN,"<sup>2</sup>"),join("",bN,"<sup>3</sup>"),join("",bN,"<sup>4</sup>")), pick(eV1Pattern[1],"",join("",bV1),join("",bV1,bV1)), pick(eV2Pattern[1],"",join("",bV2),join("",bV2,bV2)));
ans=[join("",pow(bN,eN)),join("",bV1),join("",eV1),join("",bV2),join("",eV2)];
a={-100:100};
b={-100:100};
c={-100:100};
d={-100:100};
r={-100:100};
s={-100:100};
t={-100:100};
x={-100:100};
FB1=join("",pick(eN,"",join("",bN),join("",bN,"·",bN),join("",bN,"·",bN,"·",bN),join("",bN,"·",bN,"·",bN,"·",bN),join("",bN,"·",bN,"·",bN,"·",bN,"·",bN),join("",bN,"·",bN,"·",bN,"·",bN,"·",bN,"·",bN)),"·",pick(eV1,"",join("",bV1),join("",bV1,"·",bV1),join("",bV1,"·",bV1,"·",bV1),join("",bV1,"·",bV1,"·",bV1,"·",bV1)),"·",pick(eV2,"",join("",bV2),join("",bV2,"·",bV2),join("",bV2,"·",bV2,"·",bV2),join("",bV2,"·",bV2,"·",bV2,"·",bV2)));
y={-100:100};
z={-100:100};
]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>10</text>
 </answertype>
 <numbox>
  <text>3</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[pow(bN,eN),eV1,eV2]</text>
 </answer>
 <vars2>
  <text><![CDATA[crit1=(_0==pow(bN,eN))*.4;
crit2=((_1==eV1)&&(_2==eV2))*.6;]]></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table><tbody><tr><td>{_0}</td><td>{bV1}<sup>{_1}</sup></td><td>{bV2}<sup>{_2}</sup></td></tr></tbody></table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361059  -->
  <question type="formulas">
    <name>
      <text>TL62- Square root in answer</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Calculate x:&nbsp; &nbsp; \( \sqrt{x} \) = {number}</p>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">&nbsp;\( \sqrt{x} \) = {number}<br></p><p dir="ltr" style="text-align: left;">&nbsp;<span class="" style="color: rgb(255, 51, 102);"><strong>\( \sqrt{{numberSqu}} \)</strong></span> = {number}<br></p><p dir="ltr" style="text-align: left;"><strong>x={numberSqu}</strong></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>number={2:12:1};</text>
</varsrandom>
<varsglobal><text>numberSqu=number*number;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>numberSqu</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">x={_0}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361060  -->
  <question type="formulas">
    <name>
      <text>TL62- Square root of 1</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{question}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What number used as a factor {exponent} times equals {=pow(base,exponent)}?</p><p dir="ltr" style="text-align: left;">{base}<sup>{exponent}</sup>={factors} = {=pow(base,exponent)}</p><p dir="ltr" style="text-align: left;"><strong>1 raised to <span class="" style="color: rgb(204, 51, 255);">any power</span> equals 1.</strong></p><p dir="ltr" style="text-align: left;"><strong><br></strong></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>exponent={2:10:1}</text>
</varsrandom>
<varsglobal><text><![CDATA[base=1;

question=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>base</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361061  -->
  <question type="formulas">
    <name>
      <text>TL62- Square roots</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Simplify:&nbsp; {question}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What number used as a factor {exponent} times equals {=pow(base,exponent)}?</p><p dir="ltr" style="text-align: left;">{base}<sup>{exponent}</sup>={factors} = {=pow(base,exponent)}</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};</text>
</varsrandom>
<varsglobal><text><![CDATA[base=pair[0];
exponent=pair[1];
question=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>base</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361062  -->
  <question type="formulas">
    <name>
      <text>TL62- squares and square roots</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Use the numbers to make a true statement.</p>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
    /*
                                  actualWidth    width of the input
                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><span style="font-size: 0.9375rem;">&nbsp;</span><span class="" style="font-size: 0.9375rem; color: rgb(255, 51, 102);"><strong>\( \sqrt{{numberSqu}} \)</strong></span><span style="font-size: 0.9375rem;"> = {number}</span></p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>number={2:12:1};
order=shuffle([0,1,2,3]);
offset=shuffle([-3,-2,-1,1,2,3]);</text>
</varsrandom>
<varsglobal><text>numberW1=number+offset[0];
numberW2=number+offset[1];
numberSqu=number*number;
choice=[number,numberSqu,numberW1,numberW2];
choices=[choice[order[0]],choice[order[1]],choice[order[2]],choice[order[3]]];
ansArray=[-1,-1];
for (i:[0:4]) {
 ansArray[0]=(order[i]==0)?i:ansArray[0];
 ansArray[1]=(order[i]==1)?i:ansArray[1];
}</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[ansArray[0],ansArray[1]]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[(order[_0] == 1) && (order[_1] == 0)]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<table>
    <tbody>
        <tr>
            <td>√
            </td>
            <td style="border-top:1px solid black">{_0:choices:MCE}</td>
          <td>&nbsp;= {_1:choices:MCE}</td>
        </tr>
    </tbody>
</table>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361069  -->
  <question type="formulas">
    <name>
      <text>TL62-alg expression- 3rd-5th root of number (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate {question}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What number used as a factor {exponent} times equals {=pow(base,exponent)}?</p><p dir="ltr" style="text-align: left;">{base}<sup>{exponent}</sup>={factors} = {=pow(base,exponent)}</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};</text>
</varsrandom>
<varsglobal><text><![CDATA[base=pair[0];
exponent=pair[1];
question=pick(exponent==2,join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>base</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L63- Quadrilateral Family</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 361081  -->
  <question type="formulas">
    <name>
      <text>Quadrilateral Table</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Fill in the table to identify the properties of the {=quadrilateral[shape]}.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[{=quadrilateral[shape]}:
<table><tbody><tr><td><jsxgraph width="400" height="200">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [0,5,10,0], showCopyright: false, showNavigation: false });
    var p1=board.create('point',[{x1},{y1}],{name:"",size:"1"});
    var p2=board.create('point',[{x2},{y2}],{name:"",size:"1"});
    var p3=board.create('point',[{x3},{y3}],{name:"",size:"1"});
    var p4=board.create('point',[{x4},{y4}],{name:"",size:"1"});
    var outside = board.create('polygon', [p1, p2, p3, p4],{strokeColor:"#00FF00",fillColor:"#005566"});</jsxgraph></td><td>Parallel sides:  {=parallel[answers[0]]}<br>&nbsp;Congruent Sides:  {=congruent[answers[1]]}<br>&nbsp;Right Angles:  {=right[answers[2]]}</td></tr></tbody></table>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>shape={0:3:1};
</text>
</varsrandom>
<varsglobal><text><![CDATA[quadrilateral=["rectangle","square","rhombus","parallelogram","trapezoid"];
parallel=["0 parallel sides","exactly 1 pair of parallel sides","exactly 2 pairs of parallel sides"];
congruent=["No congruent sides","opposite sides congruent","All sides congruent"];
right=["not required to have right angles","Must have 4 right angles"];
answers=pick(shape,[2,1,1],[2,2,1],[2,2,0],[2,1,0],[1,0,0]);
points=pick(shape,[1,1,1,4,9,4,9,1],[1,1,1,4,4,4,4,1],[.5,2.5,2.5,4.5,4.5,2.5,2.5,0.5],[1,1,3,4,9,4,7,1],[1,1,4,4,9,1,6,4]);
x1=points[0];
y1=points[1];
x2=points[2];
y2=points[3];
x3=points[4];
y3=points[5];
x4=points[6];
y4=points[7];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>3</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>answers</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<strong>Parallel sides:</strong>&nbsp;&nbsp;{_0:parallel:MCE}<br><strong>
            Congruent Sides:&nbsp;</strong>&nbsp;{_1:congruent:MCE}<br><strong>
            Right Angles:</strong>&nbsp; {_2:right:MCE}]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
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</answers>
  </question>

<!-- question: 361088  -->
  <question type="formulas">
    <name>
      <text>TL63- Missing Angles - Square</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[&lt;A = {factor}x,&nbsp; &lt;B = {factor}x,&nbsp; &lt;C = {factor}x,&nbsp; &nbsp;and&nbsp;&lt;D = {factor}x<br>Find the value of x, then find the value of each angle.

<table>
    <tbody>
        <tr>
            <td rowspan="6">
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                    var p1=board.create('point',[{x1},{y1}],{name:"",size:"1",fixed:true});
                    var tA=board.create('text',[{x1}-.25,{y1},"A"],{fixed:true});
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                    var p3=board.create('point',[{x3},{y3}],{name:"C",size:"1",fixed:true});
                    var p4=board.create('point',[{x4},{y4}],{name:"D",size:"1",fixed:true});
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            </td>
        </tr>
        <tr>
            <td>{#x}</td></tr><tr>
          <td>{#A}</td></tr><tr><td>{#B}</td></tr><tr><td>{#C}</td></tr><tr><td>{#D}</td></tr>
  </tbody></table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">The sum of the angles of a square = 360 degrees.</p>
<table>
    <tbody>
        <tr>
            <td>4({factor}x) = 360</td>
            <td></td>
            <td>Multiplying {factor}x times 4 <br>is the same as adding <br>{factor}x four times.</td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 51, 102);">{=4*factor}</span>x = 360</td>
            <td></td>
            <td>Multiply <span class="" style="color: rgb(255, 51, 102);">4 times {factor}</span></td>
        </tr><tr>
            <td><span>\(\frac{{=4*factor}</span>x}{{=4*factor}}\) = \(\frac{360}{{=4*factor}}\)</td>
            <td></td>
            <td>Divide both sides by&nbsp;{=4*factor}</td>
        </tr><tr>
            <td>x = {=360/(4*factor)}</td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>
<p dir="ltr" style="text-align: left;"><br></p>]]></text>
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    <defaultgrade>5.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
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    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
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      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>factor={2,3,4,5};</text>
</varsrandom>
<varsglobal><text><![CDATA[x=90/factor;
angleA=90;
angleB=90;
angleC=90;
angleD=90;


quadrilateral="square";
points=[1,1,1,4,4,4,4,1];

x1=points[0];
y1=points[1];
x2=points[2];
y2=points[3];
x3=points[4];
y3=points[5];
x4=points[6];
y4=points[7];]]></text>
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<answernumbering><text>abc</text>
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</answers>
  </question>

<!-- question: 361087  -->
  <question type="formulas">
    <name>
      <text>TL63- Missing Angles - trapezoid</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The shape is not drawn to scale.<br>&lt;A is a right angle,&nbsp; &lt;B is a right angle,&nbsp; &lt;C = x<sup>o</sup>,&nbsp; &nbsp;and&nbsp;&lt;D = (x-{=angC-angD})<sup>o</sup><br>Find the value of x, then find the value of each angle.

<table>
    <tbody>
        <tr>
            <td rowspan="6">
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                    var p4=board.create('point',[{x4},{y4}],{name:"D",size:"1",fixed:true});
                    var outside = board.create('polygon', [p1, p2, p3, p4],{strokeColor:"#00FF00",fillColor:"#005566"});</jsxgraph>
            </td>
        </tr>
        <tr>
            <td>{#x}</td></tr><tr>
          <td>{#A}</td></tr><tr><td>{#B}</td></tr><tr><td>{#C}</td></tr><tr><td>{#D}</td></tr>
  </tbody></table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">The sum of the angles of a quadrilateral is 360 degrees.&nbsp; A trapezoid is a quadrilateral.</p>
<table>
    <tbody>
        <tr>
            <td>90 + 90 + x + (x-{=angC-angD}) = 360</td>
            <td></td>
            <td>Write an equation showing the sum of the angle measures is 360 degrees.</td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 51, 102);">180 </span>+ x + (x-{=angC-angD})= 360</td>
            <td></td>
            <td>Add&nbsp;<span class="" style="color: rgb(255, 51, 102);">90 + 90</span></td>
        </tr>
        <tr>
            <td><span></span><span>180&nbsp;</span>+ <span class="" style="color: rgb(51, 102, 255);">2x - {=angC-angD}</span>= 360</td>
            <td></td>
            <td>Combine the variable terms: x + (x-{=angC-angD}) = 2x - {=angC-angD}</td>
        </tr>
        <tr>
            <td><span>2x +&nbsp;<span class="" style="color: rgb(152, 202, 62);">{=180 -(angC-angD)}</span></span>= 360</td>
            <td></td>
            <td><span>Subtract the numbers:&nbsp; <span class="" style="color: rgb(51, 255, 102);">180&nbsp;</span></span><span class="" style="color: rgb(51, 255, 102);">- {=(angC-angD)}</span></td>
        </tr>
        <tr>
            <td><span>2x </span>= {=360-(180-(angC-angD))}</td>
            <td></td>
            <td><span>Subtract </span>{=180 -(angC-angD)} from both sides<span class="" style="color: rgb(51, 255, 102);"></span></td>
        </tr>
        <tr>
            <td><span>x </span>= {x}</td>
            <td></td>
            <td>Divide both sides by 2</td>
        </tr>
        <tr>
            <td><span><br></span></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>
<p dir="ltr" style="text-align: left;"><br></p>]]></text>
    </generalfeedback>
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    <penalty>0.3333333</penalty>
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    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>angC={100:150:10};</text>
</varsrandom>
<varsglobal><text><![CDATA[angD=180-angC;
angleA=90;
angleB=90;
angleC=angC;
angleD=angD;
x=angC;

quadrilateral="trapezoid";
points=[1,1,1,4,6,4,9,1];

x1=points[0];
y1=points[1];
x2=points[2];
y2=points[3];
x3=points[4];
y3=points[5];
x4=points[6];
y4=points[7];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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  </question>

<!-- question: 361086  -->
  <question type="formulas">
    <name>
      <text>TL63- Quadrilateral Table</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Fill in the table to identify the properties of the {=quadrilateral[shape]}.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[{=quadrilateral[shape]}:
<table><tbody><tr><td><jsxgraph width="400" height="200">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [0,5,10,0], showCopyright: false, showNavigation: false });
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    var p2=board.create('point',[{x2},{y2}],{name:"",size:"1"});
    var p3=board.create('point',[{x3},{y3}],{name:"",size:"1"});
    var p4=board.create('point',[{x4},{y4}],{name:"",size:"1"});
    var outside = board.create('polygon', [p1, p2, p3, p4],{strokeColor:"#00FF00",fillColor:"#005566"});</jsxgraph></td><td>Parallel sides:  {=parallel[answers[0]]}<br>&nbsp;Congruent Sides:  {=congruent[answers[1]]}<br>&nbsp;Right Angles:  {=right[answers[2]]}</td></tr></tbody></table>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>shape={0:3:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[quadrilateral=["rectangle","square","rhombus","parallelogram","trapezoid"];
parallel=["0 parallel sides","exactly 1 pair of parallel sides","exactly 2 pairs of parallel sides"];
congruent=["No congruent sides","opposite sides congruent","All sides congruent"];
right=["not required to have right angles","Must have 4 right angles"];
answers=pick(shape,[2,1,1],[2,2,1],[2,2,0],[2,1,0],[1,0,0]);
points=pick(shape,[1,1,1,4,9,4,9,1],[1,1,1,4,4,4,4,1],[1,2.5,5,4.5,9,2.5,5,.5],[1,1,3,4,9,4,7,1],[1,1,4,4,9,1,6,4]);

x1=points[0];
y1=points[1];
x2=points[2];
y2=points[3];
x3=points[4];
y3=points[5];
x4=points[6];
y4=points[7];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>3</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>answers</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<strong>Parallel sides:</strong>&nbsp;&nbsp;{_0:parallel:MCE}<br><strong>
            Congruent Sides:&nbsp;</strong>&nbsp;{_1:congruent:MCE}<br><strong>
            Right Angles:</strong>&nbsp; {_2:right:MCE}]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361089  -->
  <question type="formulas">
    <name>
      <text>TL63-Parallelogram- missing angle</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[&lt;A = {=angles[0]}<sup>o</sup>,&nbsp; &lt;B = {=angles[1]}<sup>o</sup>,&nbsp; &lt;C = {=angles[2]}<sup>o</sup>,&nbsp; &nbsp;and&nbsp;&lt;D = {=angles[3]}<sup>o</sup><br>Find the value of x, then find the value of each angle.

<table>
    <tbody>
        <tr>
            <td rowspan="6">
                <jsxgraph width="400" height="200">
                    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [0,5,10,0], showCopyright: false, showNavigation: false });
                    var p1=board.create('point',[{x1},{y1}],{name:"",size:"1",fixed:true});
                    var tA=board.create('text',[{x1}-.25,{y1},"A"],{fixed:true});
                    var p2=board.create('point',[{x2},{y2}],{name:"B",size:"1",fixed:true});
                    var p3=board.create('point',[{x3},{y3}],{name:"C",size:"1",fixed:true});
                    var p4=board.create('point',[{x4},{y4}],{name:"D",size:"1",fixed:true});
                    var outside = board.create('polygon', [p1, p2, p3, p4],{strokeColor:"#00FF00",fillColor:"#005566"});</jsxgraph>
            </td>
        </tr>
        <tr>
            <td><br></td></tr>
  </tbody></table>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">The opposite angles are congruent, therefore the measure of Angle {angle} is {ans}.</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>small={45:80};
missing={0,1,2,3};</text>
</varsrandom>
<varsglobal><text><![CDATA[large=180-small;
angles=[pick(missing==0,join("",small),"x"), pick(missing==1,join("",large),"x"), pick(missing==2,join("",small),"x"), pick(missing==3,join("",large),"x")];
quadrilateral="parallelogram";


points=[1,1,3,4,9,4,7,1];
angle=pick(missing,"A","B","C","D");
ans=pick(missing,small,large,small,large);
x1=points[0];
y1=points[1];
x2=points[2];
y2=points[3];
x3=points[4];
y3=points[5];
x4=points[6];
y4=points[7];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">The measure of angle {angle} is {_0}<sup>o</sup></p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361090  -->
  <question type="multichoice">
    <name>
      <text>L63-Number06 What is a Rhombus</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p><span style="font-size: 0.9375rem;">What are the properties of a rhombus?</span><br></p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <single>false</single>
    <shuffleanswers>true</shuffleanswers>
    <answernumbering>none</answernumbering>
    <showstandardinstruction>1</showstandardinstruction>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
    <answer fraction="20" format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">a 4-sided polygon</p>]]></text>
      <feedback format="html">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="20" format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">opposite sides are&nbsp;≡ (congruent).</p>]]></text>
      <feedback format="html">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="20" format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">opposite sides are || (parallel).&nbsp;</p>]]></text>
      <feedback format="html">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="20" format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">all sides are&nbsp;&nbsp;≡ (congruent).</p>]]></text>
      <feedback format="html">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="0" format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">has 4 right angles</p>]]></text>
      <feedback format="html">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="20" format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">is a parallelogram</p>]]></text>
      <feedback format="html">
        <text></text>
      </feedback>
    </answer>
  </question>

<!-- question: 361085  -->
  <question type="wordselect">
    <name>
      <text>TL63- parallelogram is also a</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Choose all the names that describe a parallelogram:<br>
[[quadrilateral]] [rectangle] [rhombus]  
[[parallelogram]] [trapezoid]&nbsp; [square]</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">A rectangle is a quadrilateral, parallelogram and rectangle.</p>]]></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <introduction><![CDATA[<p dir="ltr" style="text-align: left;">Choose all of the names of a parallelogram.</p>]]></introduction>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <answer fraction="100" format="moodle_auto_format">
      <text>[quadrilateral</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>rectangle</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>rhombus</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[parallelogram</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>trapezoid</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>square</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <!-- Wordselect release:2.48 version:2022020500 Moodle version:2021051705 release:3.11.5 (Build: 20220117) -->
    <correctfeedback format="moodle_auto_format">
      <text></text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
  </question>

<!-- question: 361084  -->
  <question type="wordselect">
    <name>
      <text>TL63- rectangle is also a</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Choose all the names that describe a rectangle:<br>
[[quadrilateral]] [[rectangle]] [rhombus]  
[[parallelogram]] [trapezoid]&nbsp; [square]</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">A rectangle is a quadrilateral, parallelogram and rectangle.</p>]]></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <introduction><![CDATA[<p dir="ltr" style="text-align: left;">Choose all of the names of a rectangle.</p>]]></introduction>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <answer fraction="100" format="moodle_auto_format">
      <text>[quadrilateral</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[rectangle</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>rhombus</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[parallelogram</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>trapezoid</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>square</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <!-- Wordselect release:2.48 version:2022020500 Moodle version:2021051705 release:3.11.5 (Build: 20220117) -->
    <correctfeedback format="moodle_auto_format">
      <text></text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
  </question>

<!-- question: 361083  -->
  <question type="wordselect">
    <name>
      <text>TL63- rhombus is also a</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Choose all the names that describe a rhombus:<br>
[[quadrilateral]] [rectangle] [[rhombus]]  
[[parallelogram]] [trapezoid]&nbsp; [square]</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">A rhombus is an equilateral (all sides congruent) parallelogram.&nbsp; All 4-sided polygons are quadrilaterals.&nbsp; A rhombus is a quadrilateral, parallelogram, and rhombus.</p>]]></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <introduction><![CDATA[<p dir="ltr" style="text-align: left;">Choose all of the names of a rhombus.</p>]]></introduction>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <answer fraction="100" format="moodle_auto_format">
      <text>[quadrilateral</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>rectangle</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[rhombus</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[parallelogram</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>trapezoid</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>square</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <!-- Wordselect release:2.48 version:2022020500 Moodle version:2021051705 release:3.11.5 (Build: 20220117) -->
    <correctfeedback format="moodle_auto_format">
      <text></text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
  </question>

<!-- question: 361082  -->
  <question type="wordselect">
    <name>
      <text>TL63- Square is also a</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Choose all the names that describe a square:<br>
[[quadrilateral]] [[rectangle]] [[rhombus]]  
[[parallelogram]] [trapezoid]&nbsp; [[square]]</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">A square is a quadrilateral, parallelogram, rectangle, rhombus, and square.</p><p dir="ltr" style="text-align: left;">A square is not a trapezoid since it has two pairs of parallel sides.&nbsp; A trapezoid can only have 1 pair of parallel sides.</p>]]></text>
    </generalfeedback>
    <defaultgrade>5.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <introduction><![CDATA[<p dir="ltr" style="text-align: left;">Choose all of the names of a square.</p>]]></introduction>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <answer fraction="100" format="moodle_auto_format">
      <text>[quadrilateral</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[rectangle</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[rhombus</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[parallelogram</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>trapezoid</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <answer fraction="100" format="moodle_auto_format">
      <text>[square</text>
      <feedback format="moodle_auto_format">
        <text></text>
      </feedback>
    </answer>
    <delimitchars>[]</delimitchars>
    <wordpenalty>0.2000000</wordpenalty>
    <!-- Wordselect release:2.48 version:2022020500 Moodle version:2021051705 release:3.11.5 (Build: 20220117) -->
    <correctfeedback format="moodle_auto_format">
      <text></text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L62- Exponents and Square Root/L62-Expressions with Exponents and Roots</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 361109  -->
  <question type="formulas">
    <name>
      <text>L62 - (a+b x d)2+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b} x {d})<sup>2&nbsp;</sup>+ {c}</h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                  checkWidth     width at which the box becomes wider
                                  defaultWidth   default width of the box
                                  c, ctx             see https://www.w3schools.com/tags/canvas_measuretext.asp
                                  size               size of the font w/ px, e.g. '14 px'
                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                                      since it is always transformed into px units
                                  sizeN              size of the font w/o px, e.g. '14'
                                  family            family of the font, eg. "Times New Roman", Times, serif
                                  txt                 text of the input, e.g. '123456'
                */
    var defaultWidth = 30;
    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
        var sizeN = Number(size.substring(0, size.length - 2));
        var family = $(".formulas_number").css('font-family');
        var c = document.getElementById("canvas_1");
        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
        var actualWidth = ctx.measureText(txt).width;
        var checkWidth = defaultWidth - sizeN;
        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
        } else {
            $(".formulas_number").width(defaultWidth);
        }
    }
    $(document).ready(function() {
        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
            newWidth();
        });
    });
</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td width="25%">
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 51, 51);">{a} + </span>{b} x {d}</span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; Multiplication comes first.<br>
                <p><span>Multiply&nbsp;<span class="" style="color: rgb(255, 51, 102);">{b} x {d}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{a} + </span><span class="" style="color: rgb(51, 102, 255);">{=b*d}</span></span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>Now simplify the addition in the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(51, 102, 255);">{a} + {=d*b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b*d})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b*d}</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style=" color: rgb(51, 255, 102);">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};
d={1:5:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b*d,2)+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
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<text></text>
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  </question>

<!-- question: 361111  -->
  <question type="formulas">
    <name>
      <text>L62 - (a+b)2+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b})<sup>2&nbsp;</sup>+ {c}</h3>
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b}</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 255, 102);">{=pow(a+b,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=pow(a+b,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="font-size: 1.64062rem; color: rgb(51, 255, 102);">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b,2)+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
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  </question>

<!-- question: 361112  -->
  <question type="formulas">
    <name>
      <text>L62 - (a+b)2+cd</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b})<sup>2 </sup>+&nbsp;{c}({d})</h3>
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      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>({a} + {b})<sup>2&nbsp;</sup>+ {c}({d})</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td><br>
                <p><span>Add&nbsp;<span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}({d})</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p>Exponents:&nbsp;&nbsp;<span class="" style="color: rgb(51, 102, 255);">({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p>({=pow(a+b,2)})+ <span class="" style="color: rgb(51, 255, 102);">{c}({d})</span></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span><span class="" style=""><span class="" style="">Multiply&nbsp;</span></span></span><span class="" style="color: rgb(51, 255, 102);">{c}({d})</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(255, 204, 51);">({=pow(a+b,2)})</span><span style="font-size: 1.64062rem; color: rgb(255, 204, 51);" class="">&nbsp;</span><span class="" style="color: rgb(255, 204, 51);">+&nbsp;</span><span class="" style="color: rgb(255, 204, 51);">{=c*d}</span></p><span class="" style="color: rgb(51, 255, 102);"></span><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(255, 204, 51);">{=pow(a+b,2)}</span><sup><span class="" style="color: rgb(255, 204, 51);">&nbsp;</span></sup><span class="" color:="" rgb(255,="" 204,="" 51);"="">+ {=d*c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};
d={1:5:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b,2)+c*d;</text>
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<answernumbering><text>abc</text>
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  </question>

<!-- question: 361113  -->
  <question type="formulas">
    <name>
      <text>L62 - a - (b+c)2 D (de)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a} - ({b} + {c})<sup>2</sup> \(\div\) ({d} \(\cdot\) {e})</h3>
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    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p>{a} - (<span class="" style="color: rgb(255, 51, 102);">{b} + {c}</span>)<sup>2</sup> \(\div\) ({d} \(\cdot\) {e})</p>

            </td>
            <td></td>
            <td>
                <p><span>Inside Parentheses Add:&nbsp; <span class="" style="color: rgb(255, 51, 102);">{b} + {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p>{a} - (<span class="" style="color: rgb(51, 51, 51);">{b} + {c}</span>)<sup>2</sup> \(\div\) (<span class="" style="color: rgb(51, 102, 255);">{d} \(\cdot\) {e}</span>)</p>

            </td>
            <td></td>
            <td>
                <p><span>Inside Parentheses Multiply:&nbsp;</span><span class="" style="color: rgb(51, 102, 255);">{d} \(\cdot\) {e}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p>{a} - <span class="" style="color: rgb(152, 202, 62);">({=b+c})</span><sup><span class="" style="color: rgb(152, 202, 62);">2</span></sup> \(\div\) ({=d*e})</p>
            </td>
            <td>

            </td>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);">
                        </span></p><p><span class="" style="color: rgb(51, 51, 51);">Exponents&nbsp;</span><span class="" style="color: rgb(152, 202, 62);">({=b+c})</span><sup><span class="" style="color: rgb(152, 202, 62);">2</span></sup></p>
                    <p></p>

            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png?time=1624662812978" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"><br></td>
        </tr>
        <tr>
            <td>
                <p>{a} - <span class="" style="color: rgb(255, 204, 51);">{=pow(b+c,2)} \(\div\) ({d} \(\cdot\) {e})</span></p>

            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p></p>
                <p>Divide: <span class="" style="color: rgb(255, 204, 51);">({=pow(b+c,2)} \(\div\) ({d} \(\cdot\) {e})</span></p><span class="" style="color: rgb(51, 255, 102);"></span>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(204, 51, 255);">{a} - {=pow(b+c,2)/(d*e)}</span></p>

            </td>
            <td>

            </td>
            <td>
                <p>Subtract <span class="" style="color: rgb(204, 51, 255);">{a} - {=pow(b+c,2)/(d*e)}</span></p>
            </td>
            <td style="text-align: left;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr> </tr>


        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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xPO+2filBexvr1n27sttubjeeYELvCgvxNFuTnG5c2HnnkiSJVGWeddbOlRSwh7hZa+cuNa0r1dZdrGtdcUxVsvzIbLmxy992vMTvmGBdb2tXN9PlyOmFdsHk9F1g9V1kd+GeRpaOe1VkRfPXVH7O011q62YVN4Z+wK/5PGauMKwvy/zRdlWsmWZ+4Y9H79uabv1mMgDzWr/+8jYurjbNsXCyxPCuezJsvVxTFnZGmsbor2HbffcgCjzg5rml88IP5n6I6/PBLG7vu+hbj20y0zTBhMte42PKsaNx554NFqjLuvPP7RfprLO2gcYmlX92sJ1//VLnGRMkXitod9933S7PhvCZ32+1Ks+Em4yJLOxU7yFcXbF7POVbP5VbHLONCS0c9qxrf/e5vilQtnHnmeyztpcZrLe0849IivduVPjxx332P2nfLjKRZYVxlbNeG1ZOqT9wRSd8ua3tSFbjzzh82jjhigY2J2cYFlme5caVxWx4f2AV9jrWoMb31WO0PxpD6ZEehaazuCrbddhuyBUmcHNeURELgnnt+2nj6009v7LLLucZLTJRcZ1xo6ZcZVzfOOmukSFnGww//ztKfY7zc0s8q8qxq1pOvf6pc07jqqrpg22WX8wpeaTbcZFxkaVc30+fLGY/kqws2r6PaXupZZT66w/zRWjQ/97l7Ld3FRvw50zjP0i0p0rtdVey66xzjbON8O77UuPLJtGXSJxOvT9wRSd+uaMyf/5ViJLTHww//e2P9+q/Y2GCOMHYZY8zXbXOMPP64vyeSv2ed9XH7bnnBiDEa19PLNRZvWzv7H//4/fYdY4g+WWHckrFfnA6axuquYNt11yELNuJkeOaZnyqmWhnr1n3GBNsZxgtswb/CeKOlX2JcYVxjXFoSBynmzfuo5bvE8lxrnFvkWW3M2zA1rmlceWVdsD396ec1iWDbZRcXbG4DtufKGY/kqws2r8cF2y67uGDzelY1ucsuC4w3Gq+ydBcaLzbim5lGfINPw66cIJxhvMZIGQsszbIn05bt8zonVl+aX9yxuNK4rPG1r20uRtLYePjhx23Ob7AxMsfIGI65zjjeVsZLeX5ceeWnmmN6l13m2zHsDVtzeTtlzK2UuXQ7Ojvzw5VXlm9HYU0g3nqsYRwRrxRvtmeaxuquYHv609fYoiROhp/7XP2nqMBhh13eeOpTz2w87WkXGWdY2jnGZcaVxtXG5Y2PfSz/g/AbNtxned5mvMp4k6VdWuTL2zA1rm5ccUVZsG3a9Eur99yCVxQ2LDSuaqbPlzMeybe6qKEFr+OtxsuNN1qaBUbqCS42zrVj1xuvNl5jnGGcZd9jEz71svPlX2a8xPgOO04fUF6uHXyeaH1pfnHHImNhhXG+ibb8HM8B4faBD3yncfjhlLHIGHM3N+amkz5mU1xxxYiN6+uM19uxecblxqnEmZgXtDUY3+XS76js3A/V2Mv48bhPv8y2NMScGD/lvOL2QdNY3RVsT33qGhMX4sS5+slLDCk2bvxJ4ylPOct4tvFSS/dO4zzjCuMqI3lXNE466UNFjjIef/z/Ng49dEaSd6FxmXG1sWrDVLm6cfnldcH2lKec2+RTn3qF8SYjNmD7ZG0gX11QeT1vtWMI3BuNC4zUE3UtNy424j/smG2cYyQdPllp9LLz5V+QtGOWsV07ooxO60vzijse6WPGCWNhrp2Y5U+u2uHxx//LTsjutRM3xsv8ohzGVjpec/VuKXqdKS6//Hb77irjDCPjfKkR+3L5x+aGDa0nrNeu/aZ9t8RIm2PO4Mt83h2JDz/st8fQ/6efPmLf4Qf8St/n4s5Ki7ePNvOAD3zgmxavBux7+iTiYbpuiNsbTWN1V7D19FCoODGubgwO/ksxzcoYHLzdjp9lPNd4pfEm40LjKuNqI/n5//LG5s3/VuQqY2jos3b8QuMM4zzjEiN5I38njPTUtdK4ouDy5P8rGgMDny9qdSDY3HZ4hTFn/8TrgVV4HW81Xm680bjASDlRF/mWGRcZ8QOcb1xspHzqI53XW0Wr/MuM7zTONS41UiZlk28i9ZGu2v6UOV+Qr8q07siTKy9YLZO/af44Fsej3vh/mjZXfreYsyXX9qpN49mVlht5I38wrS+to5PycyQPZdH3s21ej9pC/J/FyOoM7JgMDX3N8g8aGVOMvbB7MjZNlu6/FAMD/2DfXWKMuUeMwWe5/GNz06bWfVgjI/9q3zHPIHGD+RT9kM+/Y7AsiAcGPm3f4QPiB77N+YDv8M8c40wj8fZi41XG643EH8Yg4yXNJ24/lGDbBri6dFYZIKD39PQb32IMwcWkrQouX2CGh79b5Cxj48af2vHzjO0E33hcbQvFd6yc35hNrV1A7pHYsOFnFkxGLQ02LbX/31kcdUxMsK22/F+wMn/+5Nkl4Axz48Zfmw3ftDQseC6Sqmgv2FY3+vs/VbJ9dPTH9j1lQV8E0oViIujvH0nK8YW9k/rG9r+LeHyxefNvi1Ja4EyaMgcHv2Jp8T1lEozHXsDpxwD29fbeat+7P3t73908jh9S26mfuvr6PlikHb+eqbK3971Pjrl0LADGA+0fGbmv8H0qmsOmvF3pPKMMz+v5R0but7b+rjjq7aaOGNutdk+2zeSlDMblbGvjQiv/nqK2zrFp02+sL95lZbAwM5ewLfojV2+3Sfurgu3v7bu3GweMNxjxWTcE2732HSdH1xlpL/MHH26Zcbdt0MdvioGBj9l3+AHfItrwQbW/+Rzja5YRn7FmINbwHSJ/OseJ2H12XbD5YBM7Z2/ve4ppWQb3n7lgO8fI2SsTkMlIgE4XJv6/0oL4B4qcdfT1MckvNTLpOdOq7hjkuKopGqoLZg4bN/7C2sEOW/nBCRds2A8RUgQS2hCBw+vq77+jFKjbgV3E/n7O5mcX37TgdSDYYtGgzdSzsikEU2za9LB9jy0ISNItLY5MHCMjP7D8CER2PnwBre801uvzPqj7HKHSic8D7LwMDNxheakf37JYhrgoj5ORkQeKXA7Px47PXU0hNB58AZ1tZAzF4lmtZ/JkLiCcOrElgG/7+t5r+WMXJnxbHd+ramOMPuntXdkcV+3gY4l+o83h28m01+epi0sWT/x4rdnOCVu5X8YDJ3P9/X9n+avjqTv9MDa9HSkGBj5k311kZPcZgUD78FMu/9hML+uNjHzPviNuMKeJf9EH2DAdbd0azPn3H+07/HC1kT4PQVzNx3fMS/xEPCBtOi+6N1fFrUEJtq3OoaFvF9OyjMHBD9vxvzZeYGR3ClGQnmGmZBIuMeH0qyJ3GcPDX7bj7NJdY2ShaCcYWkx3YzoBryUYHv5W8cnhgg0R1V6wIdbSHZ3xwGI1NFR/TYLX006wVQXUb+x7fPEOI0Ftodk/9ruy2mFw8FOWn91LFhS/XDV+fSxoLNxp8FxV2gGaKIaGvmpl4N+qsIg6coLtI1bnT4pPnWF0lBMJFmXaGjuGaT2TI2It3eGaCBB4/f2IBsZ2nNRUBUxdsPX2zrU6/0/xKQ+feyyUMaamIhjIg134jEUUH+LLq82Wm6x/vtMc353ARdv7LW9cnmdMUXZdqPp3HGNM8DfS5doQbYs81fR+LEVLsMVJIW0LUUGdtJe/UX9aVsryfVjsQPrOHZf2mD+pQM2VVbW5yrBhLDuiDNJgdzCXr+q7KtPy0vpz5UWZfC5fQSjvYBJn8EGsBWl+iG8YC8wDxkV6EhdtHMvOsGsybU/LSRm28f8oK2WkaVeu6JRg2+pMA1SAhwV6es4wnmkkELK1zbY2k4fBnStruS3a+beqb978iB3nsiiiiYVn7DPg6o5UAFE2OvrD5sLCrgCfx8KmTb+w8rikmxdsXPrKiTUWow0bftSsZ3T0XrO/7qMqvB7YiWD7lX3P4tIKgH19w5bus8Y7jPV32w0M/K3xfcb3G//O+CFjeu/OtUa/TFW/NJzWx4IWiw4Bysnlzxw2b36s6YORkY1Nbtz4UNtFfWjoS1YW7YnLZfQxPqBf64ItV87GjT+zdPc062rn94EB7q1stbcVcOtjqROOJdY2bfr1k21nPODLHFzADFt5CCAWKhY07IpFoC7Y8G2KaDtjPMZ2q3/xa5Qb/VZvy/iMvNjGGGA+4EfKv8p8cWOzne36OAVp+vq4VBKirSxU05MhRK1f1mbxTtOV25GeNIyO/sS+Iy2MseRMkQo2Thw2bXqkOOIgxvktDcQd6o845vVP5ISNEysfc/SD29Xf/8niaNjsbRwa+lbpRAw7+vrYmUxt4OrEP9rJ5r3N8ZHu7vL/sL239+ZavqrvUjKmo8wUcYuBX86Pvii3oRNs2PCQ5Sv7c+PG1gu72/u7bCdjZHT0p812psBvbAB429db2patubZTTiAdN319f9/8nN7aEbfTcFVovHLFlBJsW5UEihw2bNhkxxFrZxtZ6GOxKAe6MpfbxLqlKKGO/n4mHWeq3JCa7hRU7VplE6p+SW54+F/sGDtYiCLs8p2z4eGvWmDLLy4u2N7cTJcTbLkdJYRaby9n09RDXhd8iCReBtwOrbRclhlPsLHzd77xbUbqYqeD9CwE2HhNkbKFnp7TjVyipl9oOwKY/PiUOmP3bEFGsKX1xb2IrYWfwF4FYqKvjzTcm0e73N9xTyB+r8IXcPowRBt9TCCknpUmBO4vUtaxceNm8zv5sJO2eT1DQ6NFihZI621GtOE7Ai7jsjqWOuGq0kIT8HGAr2hzuf18v2FDvS0ITN/tDNEW88XrqS6eAfw2MICYYTeb9nvbvX76jN2NOGliEZzqwuL94bbhO8rEXsYePo0dt42Fhe3hJwPMrbjdgT6PcV8+8fJL4LSBuqiT+knbsi31EcLL00PmbWthTYFg6+9/V00AV8GlZy5B+5hhrnl5E4X3L3ON9rKj3ZpvbvNsGx/59975ZX38PNdsWW/pflYcGRvceuC3Y+ALYkWcEJT9R99ydaITETo6+oClp7x51obPFt92Br/NIr0VY4l9l+5O8sCGt9P7mrng8QY7EZQbM/MuB4Tr4OAXLB872NF2yqPtXl4aY2PcjIzkf7knhT9IE+Wm8crLFVN2XbCFo8XxyYMC9YUaDAxwTw7CgAUqdowITkwSBjSBokqOcVn0l0UpZYyOcj8ICzFPDTFB0p2Rll2Dg18rcrQwNPR5O0ZeFk4Ws1SoXGaB7H3ZYO2CLQQO7YiHAVZYwHh3kaoFFmlfMKMeFtBWPSxi7DDl0BK4pCWg4y/3TV6wRflc7kqDMAHuhiJlC77jySVq2hL36+BLFnJEMMGxvoCAfH2+8OOHanBnV8l9TP9XhSF+ZIG+zPqlvhPqPiQNCz9tiYVlRVvB5pfM8XlaFztL1Hep5avfHO+X2LEDX8diXh5LnbDaNwCh4r6i/YwH6kI0Rfvhpc22VuFjlcuYYVcImBXm1/yOYX8/L6VM209dsSOKAETUxxzEn5Q38bbm6bb5/KVs6mB++o5bfz+7j2PvMPsOF20OG4kRy2u+5RK4n1hQdgjtdIEsX5L0S/mMb8j4dmGAvSmGhzc0RW8n4BJ0by9jn/Lon8U2p39tdT3SZLrDxQkaMcT5S+OvkvGNTbR3rrWrdVKBkNmw4cfFpzpGRr5redjJXNLc6amCNjvrP9pPG3lYJOptCYzWWJjorSTDw+yEXW8nWu+1OvHBw02m4ApJ1Q/Dw3dbvrgVwwVPWbBxby3jlnlAX7cE+mRvPxgaIk5Eefgh1iLmcSqa6YPOb7UYGPiolUG51ROJGJeiU4JtK3JldicLbNr0c2NMToIZAYSJ7EFtLHImmAPBzxelVNC0JlyQ4JnCz+ARQkEWNAImwYCzegLGtRYEuB+oLNpoRzvBNjz8gyKVw4NhurPGgs2iicChjuA1FgweLHK14IIK+8gT7aNt7QRbiCFEFwIKu2LRnF+kbMFtoi20n0CJIOIsn7wEmljMlpWCF8jX54JtbD/QHvxAn4UfaBsLBr6fWVucyO8iJ+57RIj6Ap4TbEND/2zH2Dnk9THYiBglLwti9O2iInUL7Hi2nl4mgE9OyOTHG20PhjCkHtoc7ce2GTauy5fl/alo8uCv9MQkL9i8/W8yxutzEGv0EcKGuvBhulMRwrSbCwplYSP9xBjCZnxKvfm5lcLbjMhm3DAmYxxWBVt68zplh+Bo2VEWbJw4MG8h/g7B2n5XDLHNCRxjtrd3lvn3C80xmcLvTcPW2CHCry5UiXWBkRHEDHMOMjbp17hEnRdsqeDDZ97my0wQMdf+xf7Szivs+48VqfwS3dDQBrMXGxj7zDc/QazGGred+R+XofGHC4yqv7GFByf6+jjOuLrY0vxvK7N1ouECMuY24xWfvLM46hgYuM2+wwfEIOY2ZdEnjNPIVxVsnKATC/FTiGOfB1WxhogeHPxnay91U/bbm3bmTo4HBri3mhNUxhnj1OdDNeYF6PuhoS82fYlP+/vfWyvX53y0hfFQHZeiU4Jtq3Gi9yx0A4ODnGET2FmMEA1MNiZxy6404IGhoTvtewIFARPxQLBkYhEECHAELSbZjTZpW0EQIDp9IawLtupC7WfOCBTSImwImgQG8lBHkIlfDmjAAxr5U0HqAaozwRZnjL5TWUVLSIb/IgiSj6AduxXsbHQu2KoiouWH8Dd+QxyGH2gXIoz/z7FxVH9p8sAA94awsOG/6Gd/dUUKX+jxG2I3xAqLB/7Dz9RB385pBvUULthYPGhPBG9fuNLxNDbLl9ZAa7xhDwt0XOKkDtoe7ceu2bYIlx90Ae47/BbjwPul6mtvf+yckifajxBgEYy66Oe0j7sp1qoM8ZbuuN1ki/7NNeGTwv0Vt09g75LaOPTLvgjy8A1jkHqi3qpgYyGlDyACK8RVXbBhW3//WjsW45YTG8/L5dLUdv7f24uPw9et/qwLNuJHTrAxB+uCLcCuZG8vYxO/ME6xifwudvr61jdPbv0SKT4jLceY3/iI/+PPS5p+CPhl9zhpo/50fJVFtQtXysIG5n7YcFHTJ5Tlt5rQpvAF/XJdUYLDBRt+IC7kBBtzfF6p71xYRryOy+Xc51x+yI2dMK+fNoWv+D92X2zpq7GTMUH6WEN83g8MfK5I0QI7g319HKftUa63P/Up6OtjHKY74y4E6/NjZ2bXBZtPenF8ciPmdMPvjWPixOWT8o5BTkT6fTwsaky6EAEs5BHsg9xs/+kil8MFG4svYocAE8F5eU0YDg5+3L6nHgIzwYIFgoDA5E3rod52O2AENIJsnP2OJaBCGBJ4yzsx5KnC01fLxx7qiHzOzuur1+OLKgtU+JvAyGJG+vABdfKXvptb21X1hY5gHf3sYqMq2FoLIiSQpgsoeaIO7o8p30g+MvIt+55+ze3Y1sd7nXUhDdxPtB/7GTP4OrUn2o9diy3Q/22RswUeDGmNIYQeZ+xLrQ1lwebpqAumi3AItLS+tJ9z7ekmqSP6GDto/yzz+fcLy+vo719naejDEFb1h198bJEmhB1jKua/t60u2OgHyNhg3Pp8TOFijfoZRyz6+J5xgaAg3zVme/k9kYODn7Dv04Wf+YToaF0OHBn5tn0X8w67Y+eXMcEJE3m4Z7Qs2LDHX2VETGAeIcLCHvJzAkQ/0x7KYfzyPeUzBrA50s2s+b0ljklDGUus/R8vjjp8h4sxBfEfbaX8KJu/1BWM2yoYr+XXFg0M8DANfqBeyqGPow34jrYuLPWd31ZA25lD9DVjYllzNzFA3OjtxX7sCzFFu1IfXG3llk+u+/t5fyPlYgP1c3JQ7gMXzIhFYgR2MCbIQ9nXNHf0Uvh4oJ+okzKJ89M137YXSrBtJa6oCZbpAE+f9vYyETlDI0Aw0VnMfFJUF1AuN7mAqi5oBPrIF4sZ7x8r3zjrgo1gS7AJweYLexV9fUxQ6kFQVhfqqMPr4bsqvJ5uCbbcLx3EwtFOsLX6trP6Fljg+0SRogXvHxa+nL+jrtTvBOqqmEKIUReLFLZ6/rxgi/6JtAR26qJtUc+yTB0Itpw/Ul+Mxfplcd+9wJbYyQzBxRig36PtLbvwYxUuxFiEUsFavikbeDrawKJCO2K3Im1/lbm2bElSp/dzTpwGfBeGBZ02s/DPt+/Kux6+K8q4YtHvVLAxHyFix8ctvkkxOMgTj/gx5i++pO/wPbbMNtv/pkjtGB3lHivSMsZDfC0ujTOelvU0tCuER9hAvKCf6i/s9l93YQxhD+OAvLErTn7qIg4RX+hvvwzpafhLuhBC7OCVT0R9vISApI2LzNbyT475ZVDGMvUzlpnXpGU8M8f4y2fqIxbzf77HroVFKY7WbnZ6EkIb8EHMjepDBwg2/Ma8RlgN1kTl8PDX7XvaQXsYF/Qbggl/hJ9usv4trwvDw7ywu9z+auz3eM7ONeMC27Ej2knZ5fuEXZwTsyiT+vE9435rzLltlRJsW4ErbALUb+yfLgwNfcZsIIgQQAhKIVTq2+UuNJjMBL8QeeQhQDCZyu3KCxXyE7hago1HvavwNARYAkEEpVg4y/VQdxWevyogsHFLCrZcQOlcsFXTgby/8UHV38Gltvg9WOR2uFBGaLNQhDBfbEExJ9jiEhbjgQWjembr/88LNuyMxR9/TEywVe1pjRcYArKdn70Mxkj11yBagjX6ygVrXbDFzgULSgiSdBxU69saDFuYC+WFPIULNtrSmmfTJdi8XOqGlB2LPuKD9NQzWDpJ9b5m7MXJGWOPXdBUsCE6sJf6QxwwHlyo+Xir3zPaijmQMcAccBHrtiBygtiHnSGimG/UEbbjx6pgo1ziFLazO1fe3eLeOT9OOuYgcz7GcohN/rog9DpdqPmx8i0ZrSeYKQtRSZ7ou4gN5R3knGAbHi7vFPb3v9u+p9zYuYt+S/2EnXOLHA6e0PZ85KFsTg4+Uxx1+PzjxJO+ow+wm/ETts8tjQcX5yHMJ7NjvzOw64ItgovYnsttwOffuTU4yA2yf2V8o5EbwTlD4TIhQmZi5Ifjc+B7DyStwB6BL7+AIlJCQMQWeASKcrvaC7ZYgJmInLHW73fwNExwghKBg8md2+lgEo8l2KoCot1DAKQnQLAQEKgJTF72xMqPoNKyr7P66jsgoOXvCIa+kNXrCXKps3x274KN+ljs8KUHyfaCjXSIZNKxYKR1uT/ygo3+qo6LdnZWWX8Iov2ObM7Pwdzl2m/Y9/g6bPNFMi/YcoK10zZMJ/FB+1/k4B2BrXHjAmigcpnKhRVtTf3CHKP8ej/7uGXhjRMNH7dVO7xc/M3iHDtmnq7Vd/g/LRsxSF9jS8z3nOgIwYZgrM5Ttzsv2LCHtkY+7Albgu5TfMB70YaHv9c8+cEGpz/IVf0lDC8/FSwLmukCLaHLOEasxPyIeFav38n/3WcpXLDhh1y/BXO+Y2yHYOU1G+U40epbGDtbzLe03/jLSVHLB61xEfNmjtlYFbW0n/6N3UXGhItRLze3m5r6a7y4tzNSgm3a2dtbvjQQ8JflItZ43xcLYSyknKkx6CfG6s2iKfr6WJhJx0QOYVS/x8knJpMOMpHiLDEmc9q2bgi2ToQKn3d0wRb+dn/l6wkus0Wm/KSo/6wZ9aVCZEGtf12wYROXWjgDZlHjrDot3/2RBldQFmyxEziRADuWYGPsc/9LLPxuQ76cpbUdNn/ykzJijFNGO8FG+5ljiAYWq2r7txXS/m1ZsLFAx+44Y4FdlOg3WF6gW4KNPmrtqHdHsDH2ycO4jhOWEOKtfHBw8Ku18TMe3M+UH34s31PrbcNnjMHYMcKGdH6ELR6jWnPc/5+iO4Jtdu1BLz9OOyjbhVe538LO8i0R9XExy2ws/yyhjzP6gfGYrjPRzvKJVl2wTTSe7AyUYJt28vbtHPyBAHbWWASZCAx0JhEBhwE/UV5jIjD/VNnwMG/EZ0IRBDmr8jOfauAjf1lAdEew5RYef7EvgTCCkgRbp4KtKkRciFHf9ijYGCssJPgJwVZdoKusjyW/PDhRwUb7t23BVh1XKXxHfmsJtlRQhL/HFhQtwcbYiziEqOuWYCNfzNWcwFnR9krHeCg/Ve3tTdHyW8z3Tk48ghzfMoKtOv7dT/g2nSe58c+4qPYd7aN8TqxuMBurgg17OZ4K1jSO5ezFnrBXgq1OCbZpZ/UsJzA4yM/9xI+9MzE56ySIEaQYvBPlLAtIPy1KL2PzZt6SHZOZgOYTNbcg+KPxnQiIqQm2wUFenpheYtvxBVtv761FihZcRExMsFVfAOr3KVIfizPjaNsUbOxuVDFRwdbXV3+tSV8ftlBGp4JtrPZPhWG3j0P3T/Rlvj3tuaytwPD5zM484ybdyd4ago1ySTMRwUbZ3RRs9D35Ir7VBc7g4IYitYP7qYaHv2FlEYeZ45D2+DvJUtQF27zMJUOOx3zv5MQjyPEtI9iqO/E+1zoTbOkupPcd+Sh/LMFG+9N70tI4Np69E40nOwO7LthiQIo55m62B345lJd3EnQJqAQw7t9hYsZ1/4lyoQWlLxU11OHvTGJSxSUMDwJV1IVUTKR04YHLaguwBy6CMoGBiehn/tRTFQCjo9+377n/jgDOriLBmeARk7ZVT07oeB2xw0CQDsHHU2Tlnaz8Tg7BKhbWcsAE7cuv+6Gz+ghg9bet+y9SpDuN7fzt7O8vv/sOuGBBsMWlvhBs5XtYWoItvSSYXjqC7o+8YKO/CPaIneolj/G4LCu2fLzhq7LAb1cu9x2l8BdEp+9VCwGRE2w8JTpe+yfLZU0RQJ3+u5GUC2NMd+onZ85XgeHhuywNsSP85jfn1wUb7+djoQ2hEQs0ddT7OS88fNymKAvBarnBJU1/BPznzRjn+J6ysbn8xHNZsPmlt/I8dbur883HflWwle0p/7Zl+noL6qK9/KWMC638nGBjfMXYn1uy25925njqt6rd7cjxqiDuzL91AYQfiFfYyE+dVZ9kpRzEeLSDvq2WC8vx0C9fko82uiDjZ89SuL1xPK7MpON+PHsnGk92BkqwTSOXWWAtv8YgsGEDv/sW967F5AnBEoN2oiTvwlKQTOHCgIDCGRJnt0yoxaUzReD3Q+UWZiZfq308Ml6tq3VPEgtJKtjqTzb6QksgJEhyNk2Qow3lergHMHfPidez/Qk2fsQ5hb9UlDRj+ztY3bH1xSIEC2UQ4KmLhw62LcFGm6qC1X3ViZ99LNQFL8Kf9tOudMGeXsFWHQP8rmJvL8fwk/dHq1/dx7ly+J4TlHb3WfmrejjJoS/SnbB5NTHvr99AiKTjIhZot2Eygm1w8GP2HQt0jAViSdmPVVt80aefsT0uidJHOcEW7coJn8kJthT+zjRsp53RDoQvdl1t5Y8UKR0ep1OhM9fGXfln0lq/g+s7UO63dv2cfsf/2wm2XL8Fxxdsg4NfKY46/PUntCPGf73fsKe6G+nvzCRfjAtemp67h02CrbuUYJtGLmsbdP3pUBYZBmxnOwvjk7xLaoEk8PDDv7Xj6cLIBFlsorL8gkvg9wQxAQma2BYB0INLTqwBX3wJboipEGzerv7+jxapWvCn+wgE+ACbCEwEEK9nrIXL69lygs0XuxDUBE33l9fRygc7F2zYVn6BJHCRjL9JG/7GD2ldS7P3Q/Jj7S58WZjxIz73/NuiYONHqqvwS7rYxP13LOTxioFou+fN/XC37xpgV/jPd27IvzUFG0CM8xLWvr53WZrY1a6OobQcH0tVUZpiZIR3afGwEnMs2sHYp+yysPLXMYRgo8/S9i6rjadOBRvt8peppvXj81Z7qn3l6UOw0c+UXX4wgZ8w8n4kJuTmactHKcYXbOX5PTj4SfsOvzBHaQN1McepD6FzV5HS4elIHzte82ppWi/9HS+eR1tSlgXb8PBX7Tv8MDXB1tt7c3HU4SfJ9C2+Sh8WwYaWfWm5fkJJH9Mn+MBPECTYpoNdF2wx4MQqc5eugF8O/UtjeoYcgYkBngbziZB8PK5+e1FTHYOD/C5c7GixMC6wyThUE1/Y6Gd5MZkIyNjHu73KIiCFCxXEQ1VIMRHrL3wFHpxisfadAurh7LDdbiHwehBUcRmM4EM99bdwu10scHEGTNupJ/zNk4flnUZfvOgjbPP7C/v6uMTEguf1hM87r488/AZg+ceeAT+b1NfHJCU4Erzc37C395as31uXoPEFAZOxFIKlnWDDpgjYBNUI2Ok44n6TdoItdwk7zd+O7qve3jXZfmXB898fZIEKAUL5S8wvH8zeC+o2MdYYB9hFm5hL9FE7wTZe+yfH6hioYuPGn9tY/7al+6S1k5+doW76mPfzfbZ54pSbHyn83rW4lYLYweIYJzq0o/w6BhdWt9j3jI24J8zn18jIpiJVCz6eWETTcYud9RdXt8qOBZr5h995qWrZF/5CboQCY5X52ho/aZs9HaKA+uPkI8r1sQCr5bvNtJGY07ok3uqfsiDasOEB+w57EGKIIsYCIouXzd5eG58+xvB3CF98Un7PnPuDX38gDe1jHPo89DH8d83xyJWG6Pe0XSlcaFNfKqzIk8ad3O5kCKDw7yIra3ORwuFl499qv7kd1fve/CevKBd7IhbmXusRgi1OviPuR3zI3a9YtXci8WRnoATbtLE68AP+dCiCjeAVi1+coU5lsJIXzrfAl/9BeK87nVQEgfk2eeq7HoDLbfzEDLsEPNBQDWT83mT6I9X+4+/tBBuBvPyyxQBnfqOjP2zWMzp6v30u7zBQ78aN5TN236HsnmCrXrIF2IWQIGjFbx5yZu1tikWyvkCNXR9vsL+t5ssAPwuDH0ZGfmD8obX7l9m0LBB9fZRJPSw8+DvdCayL660v2OCC2u5EgDbRz97+e40/rNkR8EvB9H/sZMYCFONtegVbb+/6opYtA8Raby8LZvxwf12g0u7h4XuKHA586pcw3T/4vuqXQH7c5gVbgIW3rw+hcoPZN2SfN9XGq9dPmSzQsQvm87UqHBFT/usfl1h/fczaw8KOuKGffFxX59vYgi0/nv1EMezhB/dX1mwJ5AXbXEtfjpv4mku/fX2r7Tht5L7Cz1ibWrELO3zupDGkLFyB23e+2TVo/vuC8Yv2mTZFX3cm2HKxBmHuu4yMH798Ozj4Zfu+PC4Q0L29tIP2I6QjxuReLizB1n1KsE0b213WGBh4rx3nLDkd3NUzwsmSwb7QxEf+sqjf/8KZdioUPWi0e8K0HRAWvb3XNyd/wAUbQion2DzIDA1N7FcfCBr9/e9pBsIUrXsAuyPY+vqGa4EtB8SEt4uFkrbxuo52P9GVqw8/LLQ2/UMzwE8GCEl/LQq+jss1XNaJBdb9sG0JNkhaxvk8Gwf1J0Y7BWPOx3HcVpDu0DKXqKd8CQZsScGGL4aGvl7U1F24WGM+ETcYVyyOcfmXMUg/+OLY27vWxkf+hK0KTrg2bGidqPi4Ze6m47Yu2BgLnWLDhh9ZfvqIHS3sZhe4NR/YtR4P3s4QOfX55uW3E2yQWxHqJ4vMP56ArP52ZjUO+Eko9qeCjTp4gW59t3wsjI5y+wPzh5ML2oQfGDt3FynyoB6POcQ58vA7rOMJNsbF/HHLzgHf8IP1Hlsol7bHDj67wtVfOpBg6z4l2KaFuftZgN9Hlj4dyqITl7AY3PnyJkZ+IPv9RY11+KLF2aLfi9BatHgMvPwaiBz8LJLJxsJ9gU3CVLAR8GPXI+5hi4kLmZCDFkA2dCRWCPa9vZTxNquzKtioh8UrgvR4gi0WjRA2qWDDb4jJ8QPbwAD3H7KYEbh9QcsLtnb1hR/mWNsWlxbMTsBvMvoOBOXjZ8QHuyf4AF/Tl15PXrBhEwKHIDlRwYbPY9Fqf0/f2KT91HmTLQhcJsq/9iYHxszw8AbLS7tpP2QcMpYZJ/iYhdrbXxds1Rfndlew+UL2iQm1aTz4PWvsyLOzhmBmAY3+Dvu9z5ycDNw+rmhjJ7O398bSvGrN37EFG/OO+w45ARwLo6P3WlrKih0qTq4YO+k4XWTp2s8B+tzjJDs7xMrZ5uOqWGAcjC3YqK+T+e0niOXfcPV4TR0x9hlnfkmTnbkNG/K/MlMFcx2fux9oE8KGuIWtc01Al2/LSEF/+UkGeYjbc0pztL0Aws+I3E8029YJGL99ffiM8ug/+i7GnM97Cbbp4NQEG4nJRGYKMcGGc8UqueemOvnYFRka+pQd52wNoRHBi4HKhI3BOlX6wjE6+oAFu/KZIoLRL6MxAdMdGern+1l2fJ3l/aHZX17sCOb8CHDrPW2+aHIJI+D3R8RiysRlESUgYZOLKQ+miJWFVt7dVm5L8IHNmx+x+r9ndpCuVc/QUEsE+82zfA8jSLcuBfJahbTtbhc2sVinC1HYhN/wwXyr912W/sel9rMw0f7W+87SRRPh8ZEJ1hd+wOZ3WJ1cjvlOs46qkKWt3N/mvqfPWFBh2IGfWcwYRwTnGEdLzN5vFqU43P5UsKQLZ9DtSx9GwabyQxjpuA3/dUrSY6OPNxYhXqOAEKX9VTAe8KfbHm2HLA6IVfzLAoEvy+1PL0XRBn+1zXjtnyypl7Lwy0xr0z9Z/a25MREw3rh9oa8P/yAWiBmMdRZFxh39zbG4DyrtA2yYZ2MFwf7dyjj+z6ZNAwP/YGkQuhfZ/1uvHvKHX/Ar9SCCqcMFW4xvFnP34Vubc5S+YYwGEAWcaA0MfKhIR6wJsUbs4F4x+j78jv1cJv98U5Sk8Et3n7Dj5GXse7v7+z9cpPD6vB7aE2KB8ik3fNLyCz9KPzr6rzW/8MDD0NAXLA11XfzkcY75eGOuEWuwAZ/EPZaMIV5z8ZFmu+tx81fNeNrXxwLMuGP+UAcnXfgiBJvHxeHhb1kZrdtM3LbN1mZ+B5T2IdrId5N9/6siFXP78/YdfuBEGRsjHlJ2jMtrLd0Xm+WlfQaw2/uNscG8or0xVyiT+dIaD8S8gPcB6ehn5mOcqFN/jM3FHdo70XiyI3Pygm0PowRbR2TAQQY2CzWBjwDIAkvg5S+fCUCcMfoE6N5ApRwmKYGA4EWAZ2IgfiLwMxmr9ROA+D/fERQIDkxcJiFBHFIOn7GfAEkAo3zKYuL5IuAkOOeESgQnjrHwk5/Jjk3VeviOYwQ47CEYpPVwDP/6DcPejqAHUreNdpCWYEnbCA7YkPqcPAQ2jiHEqCvaT5+FXXxHObH44Gfy8beT+qp+IAgSsMhHevJSTzviE9Lge/L4IlYfR/zlM3YRQGkP/UYd6cIWC2dK8mIbdhOo8T/tIX8EZMpN65sIyUO9Md6og3LpU+rItRvG2MMWxkHsUmAnbelW+yfDqI8y6Q/Gts8hxC67mwhSTpqq4DtuJ2A3rfX7wrETH+IUu+lvxiZton9y/ue76jgOn/rJjzP1JWXzN8YWnxm3LPLhV+YTfcV8Iw0kP39jbFAm9UQdMHyezhfGPmWGvXwOe4kH2BH20nbKZbyHyMEmbKNfY77FfOA7fEOZOb+4oHa/kC/md4wvSP3BaBNjE9vScYPviZv4hnrxDXOFPNgdPojYAfEVtuLfiI9hG3bTPnxFOaQnP36gTOzFbvwUc570+IX5kB6P+RmM+Rxtpz2UX7UzGPXRZuYntqbt5i+fY42JGIEPcutatJFyxrK3Op53ZqKxpibYDjGGYHttvhLRB11MkAiaITT4S2BhoEfgJX23BirlMPAjqDFBmVAECernb0wS7EvrJ8gx0QgGHGfyhd1MRiYYwTeCIxOZdExQ6iHQkCcWlmr5Vfs4jh/Ih42UTV3Uw1+CALYS3Cif4JTWwzE+Yy/lUW6Qz7FwUjZpw+8EWAJt2JTahb30C+mog0UXW8IHtJ3yKDeCZuq3ydZH2/AneagDX+CHIPXzXYwf6sHv5KVsbMiVj10EScqmLeSNxSLyRZ40L8GVvLEQ0R7yR/DmGOWndU6EYV+MA+rBLuqh32McVNuPb+l/xlf4H1urtkyl/ZMh9cFYyLANG7GVerE9FSKcQHGpsMrYVSZdiB3ajM2MkZhT1f5O7Qi/+q5Ka34xroJ8xhcsnviGv/QzaSH9EeOW8qgz5ivpgqQlL2VRJuOT8vkbY5XysT3iXdpXOXspN+ylDPxHHdiEDdiEbZE++pT/812Mh078wngLWyH1xtzFjmgXaWPOp/ONv3zGrpjDMVdSf0fZUU6IGvKGbdgdsYD2pP6MsRvxLvom5g71Ym8cT+cnpGx8T9vpw5hrOTshx7AVP1XnGf6MdnOM9lAe9VN2jNGom/TkIw/tG8/etN92ZnZHsP2B8Y+Nr7EO+/dWp4gtMvAYzAxCBiODmIHJIGUCpIE3JkGunMmS8ig3ghMTJOrnL/bEJMFO0gfDbvJhJ/aSjwkJowzKZNEjHZOQ8kjP97nyU9uiHuzDDwSvtB6CM38JBJTF8Vw95MGGdGFJy+d7jpOOciDlhN9Tn4Vtqd9y7cemtF7KIhDxd7L1cTzalvZV+CL8wXeUTRrSpvVTVrVsmLOLdlEfPiJvmi8YdsWCQL5qu6OOXP7xGHmr44B6YgGItlfbj/34lfG1pdo/WVJnOh7oJ+rEdhbcEG9xAoQoC/KZ7zlOOhY08uF/2ouf0nGeqx+GDaSlnbQ9/ApTP3IM32Mn/od8X41P0U8xLyIt+WNOUmaM3ZgnfB99RVnt+iqdBzEOohzKrJZDWv4fc4Y86fGcf6r1YHvMt/AL/48xEr6I8mPORTuiTFj1D22nvCDl8h3l4NvUH9Vy0nET/oz82Mxx6iI/5VBetCVspI1RZpSfjsucnRHfqCvKwk/kqfqUsvgubKVd5KHcdJxG+qifY53YK5rGem2htdBcaK/9jGixjgQbiX/feJTxFcbTzPEP5isSfXAyaJlQDHoGMoOTwZpOuC01QGNCUQ/1Uy/1Y0cEDOwjXZovJhZ5mUTkx15IOfwlL8fIT7poa6SHuUlerQeShry5eiDft6sn7IhjUSZM20A6GGVF2nZ2pXlzdvFdtd6p1JfLH/WlbFd3rlyYK5f8ndrFcdJFHvJ3WnenpIxqXam/07ZH+0m3pds/WUZ7qJM6qBP7mXuxQIY4aCdKU7FDPvJj80T8Hm2PdlMGcz8YcSj6lL/h4/BzWh9/q/1DHhjfUWbEubSOTvyd2kueqr3VcsK/fBfjI45TVif1tPNLlBc+ST/n2hFlhj2kTX1R9Qd1j1dO2EaeNH/YEH0TdUZ6/lI+x9OyJ2InTMuq2lkti3Thp+gDjqXpIw92dWrvzky0FZtiTa3VkWCDTzPuZnymcV/j84wvNB5v/NOenoFP5CsTnQzAGNhVxrFcvm5xsvWneSIwVhkBI62D74Lj1QGreaPsCGjj1VM9Xi07LTfypGWl6VNG3jR/ylw5kWey9VXzp8z5I8rNlZeyWm7VrlyeYJo3zd9p3Z2Ssqp2QtodjO/S+juxoVouf7dEG3IMG9P6Y6GMBa7KOBYL31RtTW2oMo7l0sR37cqK/6dM8wfjWFrOWJxIWWna+H96fCymeXNMy6t+hmOVCavlBcfKHxyrjGr++Bzp089pmSnTNNXyU3ZazmTyRL70cy79zsqZd5vGOtX48kJzsVmGBkOLocnQZm0F2zOM+xifazzC+DLjKT09/3Nh2eFinelgrjKXvtvM1RvMpRdFsXtM51uItlSIQsRZ9btUrE11rqY2VDlWmrSMsdKNx1w5YzFXRnC8tNXjY7GatxPmyqkyly9lLk+VuXzBTtJW0+SYy1dlLl/K6cqzsxFt1fNq4x8ZjzSivdBg4wq2XY0Itr2NBxsPN77EeJLxL+xs8Df5CkVRFEVRFMXOOf9xk1pnmL462fhS4wuMzzEi2NBi4wq23Y3PNh5oPMx4nPGVxv/W0/Omm/OViqIoiqIoip3z/H9ybdVzYqG10FwHGdFgaDE0GdosdFoT/AcFt4uRm9z2NMaTovzaQfHgQc9f9fTc+NN8xaIoiqIoiuL4REsd+FbTVfHAAVqLV3rwS1N7GdFiaLInd9cCIdh4GoEtON7/wU1vXEvlmipbdVwW/fOenhde3tMz74n8tWlRFEVRFEWxPdFQp8w3TfUXxrgcygMHaC6eEEWDocXGFWxswXGzG1tybM0933iMkZe6oQT/0sqelTdCFEVRFEVRzBOx9mdrTEv9lZH3r/2J8VgjWgvNxTMEaDC0GJoMfVYSbIAvuFaKouPaKZdF431s6S7bG4yn9/S8ZLCn5/qH8gaJoiiKoiiKLaKZ0E49f238cyO7a7yJg921eP8a2gsNhhaL+9dqSHfZ2IpD4cXTooca4142Hj9lG48nG87r6XnT7f5IuiiKoiiKoljm3CdcK+0zUGin/278UyO/bsAVTB42QGuhudIX5o4r2NKnRbmOiuLjuiqPm/IUA5dGqQjRdrrxHOPbe3pOfU9Pz8Xf6OmZ9WjeYFEURVEUxR2dc/+jp+e6n/f0XP49k0ofNB12temkc43srCHWeFEuWuoPjbzvlh8q4EHP2F2Lp0Nr96+lqO6y8R4Q7mWLJ0a5NEoFIdq4PPpG41nG84wXGy8zXmHEwGuM7yg4UxRFcSfitRNgLr8oitsHQ+egedA+aCC0EJoIbfRmI1qJy6CINe5be7ExLoXyZGjcu5Y+bNCRYIt72eK3RSmI97Kloo3Lo9zTxk1z7LZhzJnGs40oyfONbzNeaLzIiOGiKIqiKIo7EtE4EM1zgREN9BYjmghtxK7a64zcs8ZlUDQUYo3XeMSDBlzRjFd5jLu7BjiY7rLFpdFUtPEQApdHue7KzXIoRYzgCVJ23P6H8S+NbzL2G9kChFy3xXhRFEVRFMUdgWgbiM7hNjG0DxoILYQmYlPrFCM/QMDPT6GduAyKlkJT8asGiLW4FIr2CrE2pmADIdiqoo0CEW1s3XG9lUdQjzJyXxvCDdXYZ8QwtvwQcCjKPzPyJl/4elEURVEUxR2EoW/QOmgetA8aCC30KiO3kCHU2FX7AyM/+ZkTa1wKjQcNxt1dSxHKLrfTxj1tPIjAEw1UinBja4+nSDGI138cb+SSKSIOY9mFgyhMURRFURTFHYGhb9A6aB60DxoILYQmQhuhkRBq3FaGduK5ALQUmirdWZuwWAuEaKOAEG1cX+WmOJ5kQBlSKZWz48arPzCIrT523o42Yijbf5AXw4miKIqiKO5IDJ2D5kH7oIG435/bx9BGbG6hlbhCiXbip6fQUl0Ra4HYZYudNm6Gi6dHUYZUymVSdtwwBIN4BQgCDiXJDXUYG+RdI6IoiqIoijsCU42D5kH7INDQQmgiLn2ikUKooZ3QUGipEGuhs2KjbNKIAigs3W2jMtRhiDd23djiQ8BhGL9FipGQnbiUiDtRFEVRFMXtkVVdE3oH7YMGQguhidBG3KcWO2rx2o7qrtqUxVogJ9qoMIQbl0oxBIMgAg4DMTSIshRFURRFUdyRmGodtA9EB6GH2NQKoRY7altMrKVIhVuIt1TApSIuhFyVGC6KoiiKorg9s6pvQvuEOIOhjVKRlgq1LYqoJBiVVwVclWG0KIqiKIrijsKc5gk9lBNpwWlFtfJgKuJSpg0QRVEURVHcnpnTOsGcPtpukDNeFEVRFEVxe6cgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCNsBenr+P/GJbf3IDe/dAAAAAElFTk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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={10:25:1};
bcde={[0,2,1,1],[2,0,2,2],[0,2,2,2],[2,0,1,1],[1,1,1,1],[1,1,2,2],[1,2,3,1],[1,2,1,3],[2,1,1,3],[2,1,3,1],[4,0,1,2],[4,0,2,2],[4,0,16,1],[4,0,8,2],[4,0,2,4],[1,3,1,2],[1,3,2,2],[1,3,16,1],[1,3,8,2],[1,3,2,4],[2,2,1,2],[2,2,2,2],[2,2,16,1],[2,2,8,2],[2,2,2,4],[3,1,1,2],[3,1,2,2],[3,1,16,1],[3,1,8,2],[3,1,2,4],[3,2,1,5],[3,2,5,1],[4,1,1,5],[1,4,5,5]};
f={1:10:1};</text>
</varsrandom>
<varsglobal><text>b=bcde[0];
c=bcde[1];
d=bcde[2];
e=bcde[3];

ans = a-(pow(b+c,2))/(d*e);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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</answers>
  </question>

<!-- question: 361119  -->
  <question type="formulas">
    <name>
      <text>L62 - ab + c(1/2)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;"><strong>{a}({b}) +</strong> \(  \sqrt{{=c*c}}\)</h3><script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) +&nbsp;<span style="font-size: 0.9375rem;">\( \sqrt{{=c*c}}\)</span></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">\( \sqrt{{=c*c}}\)&nbsp;</span></span></p><p><span><span class="" style="color: rgb(255, 51, 102);">Since {c} x {c} = {=c*c},&nbsp; &nbsp;&nbsp;<span>\( \sqrt{{=c*c}}\) = {c}</span></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> + {c}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                    </span></p>
                <p>{=a*b} + {c}</p>
                <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} + {c}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:11:1};
b={1:11:1};
c={1:12:1};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b + c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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  </question>

<!-- question: 361114  -->
  <question type="formulas">
    <name>
      <text>L62 - ab + c2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a}({b}) + {c}<sup>2</sup></h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) + <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">{c}<sup>2</sup>= {c} x {c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> + {=pow(c,2)}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                        </span></p><p>{=a*b} + {=pow(c,2)}</p>
                    <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} + {=pow(c,2)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:11:1};
b={1:11:1};
c={1:11:1};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b + pow(c,2);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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</answers>
  </question>

<!-- question: 361115  -->
  <question type="formulas">
    <name>
      <text>L62 - ab + c3</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a}({b}) + {c}<sup>3</sup></h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                  sizeN              size of the font w/o px, e.g. '14'
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) + <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">3</span></sup></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">{c}<sup>3</sup>= {c} x {c} x {c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> + {=pow(c,3)}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                        </span></p><p>{=a*b} + {=pow(c,3)}</p>
                    <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} + {=pow(c,3)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:11:1};
b={1:11:1};
c={1:11:1};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b + pow(c,3);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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<text></text>
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</answers>
  </question>

<!-- question: 361116  -->
  <question type="formulas">
    <name>
      <text>L62 - ab - c2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a}({b}) - {c}<sup>2</sup></h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                  sizeN              size of the font w/o px, e.g. '14'
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) - <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">{c}<sup>2</sup>= {c} x {c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> - {=pow(c,2)}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                        </span></p><p>{=a*b} - {=pow(c,2)}</p>
                    <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} - {=pow(c,2)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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xPO+2filBexvr1n27sttubjeeYELvCgvxNFuTnG5c2HnnkiSJVGWeddbOlRSwh7hZa+cuNa0r1dZdrGtdcUxVsvzIbLmxy992vMTvmGBdb2tXN9PlyOmFdsHk9F1g9V1kd+GeRpaOe1VkRfPXVH7O011q62YVN4Z+wK/5PGauMKwvy/zRdlWsmWZ+4Y9H79uabv1mMgDzWr/+8jYurjbNsXCyxPCuezJsvVxTFnZGmsbor2HbffcgCjzg5rml88IP5n6I6/PBLG7vu+hbj20y0zTBhMte42PKsaNx554NFqjLuvPP7RfprLO2gcYmlX92sJ1//VLnGRMkXitod9933S7PhvCZ32+1Ks+Em4yJLOxU7yFcXbF7POVbP5VbHLONCS0c9qxrf/e5vilQtnHnmeyztpcZrLe0849IivduVPjxx332P2nfLjKRZYVxlbNeG1ZOqT9wRSd8ua3tSFbjzzh82jjhigY2J2cYFlme5caVxWx4f2AV9jrWoMb31WO0PxpD6ZEehaazuCrbddhuyBUmcHNeURELgnnt+2nj6009v7LLLucZLTJRcZ1xo6ZcZVzfOOmukSFnGww//ztKfY7zc0s8q8qxq1pOvf6pc07jqqrpg22WX8wpeaTbcZFxkaVc30+fLGY/kqws2r6PaXupZZT66w/zRWjQ/97l7Ld3FRvw50zjP0i0p0rtdVey66xzjbON8O77UuPLJtGXSJxOvT9wRSd+uaMyf/5ViJLTHww//e2P9+q/Y2GCOMHYZY8zXbXOMPP64vyeSv2ed9XH7bnnBiDEa19PLNRZvWzv7H//4/fYdY4g+WWHckrFfnA6axuquYNt11yELNuJkeOaZnyqmWhnr1n3GBNsZxgtswb/CeKOlX2JcYVxjXFoSBynmzfuo5bvE8lxrnFvkWW3M2zA1rmlceWVdsD396ec1iWDbZRcXbG4DtufKGY/kqws2r8cF2y67uGDzelY1ucsuC4w3Gq+ydBcaLzbim5lGfINPw66cIJxhvMZIGQsszbIn05bt8zonVl+aX9yxuNK4rPG1r20uRtLYePjhx23Ob7AxMsfIGI65zjjeVsZLeX5ceeWnmmN6l13m2zHsDVtzeTtlzK2UuXQ7Ojvzw5VXlm9HYU0g3nqsYRwRrxRvtmeaxuquYHv609fYoiROhp/7XP2nqMBhh13eeOpTz2w87WkXGWdY2jnGZcaVxtXG5Y2PfSz/g/AbNtxned5mvMp4k6VdWuTL2zA1rm5ccUVZsG3a9Eur99yCVxQ2LDSuaqbPlzMeybe6qKEFr+OtxsuNN1qaBUbqCS42zrVj1xuvNl5jnGGcZd9jEz71svPlX2a8xPgOO04fUF6uHXyeaH1pfnHHImNhhXG+ibb8HM8B4faBD3yncfjhlLHIGHM3N+amkz5mU1xxxYiN6+uM19uxecblxqnEmZgXtDUY3+XS76js3A/V2Mv48bhPv8y2NMScGD/lvOL2QdNY3RVsT33qGhMX4sS5+slLDCk2bvxJ4ylPOct4tvFSS/dO4zzjCuMqI3lXNE466UNFjjIef/z/Ng49dEaSd6FxmXG1sWrDVLm6cfnldcH2lKec2+RTn3qF8SYjNmD7ZG0gX11QeT1vtWMI3BuNC4zUE3UtNy424j/smG2cYyQdPllp9LLz5V+QtGOWsV07ooxO60vzijse6WPGCWNhrp2Y5U+u2uHxx//LTsjutRM3xsv8ohzGVjpec/VuKXqdKS6//Hb77irjDCPjfKkR+3L5x+aGDa0nrNeu/aZ9t8RIm2PO4Mt83h2JDz/st8fQ/6efPmLf4Qf8St/n4s5Ki7ePNvOAD3zgmxavBux7+iTiYbpuiNsbTWN1V7D19FCoODGubgwO/ksxzcoYHLzdjp9lPNd4pfEm40LjKuNqI/n5//LG5s3/VuQqY2jos3b8QuMM4zzjEiN5I38njPTUtdK4ouDy5P8rGgMDny9qdSDY3HZ4hTFn/8TrgVV4HW81Xm680bjASDlRF/mWGRcZ8QOcb1xspHzqI53XW0Wr/MuM7zTONS41UiZlk28i9ZGu2v6UOV+Qr8q07siTKy9YLZO/af44Fsej3vh/mjZXfreYsyXX9qpN49mVlht5I38wrS+to5PycyQPZdH3s21ej9pC/J/FyOoM7JgMDX3N8g8aGVOMvbB7MjZNlu6/FAMD/2DfXWKMuUeMwWe5/GNz06bWfVgjI/9q3zHPIHGD+RT9kM+/Y7AsiAcGPm3f4QPiB77N+YDv8M8c40wj8fZi41XG643EH8Yg4yXNJ24/lGDbBri6dFYZIKD39PQb32IMwcWkrQouX2CGh79b5Cxj48af2vHzjO0E33hcbQvFd6yc35hNrV1A7pHYsOFnFkxGLQ02LbX/31kcdUxMsK22/F+wMn/+5Nkl4Axz48Zfmw3ftDQseC6Sqmgv2FY3+vs/VbJ9dPTH9j1lQV8E0oViIujvH0nK8YW9k/rG9r+LeHyxefNvi1Ja4EyaMgcHv2Jp8T1lEozHXsDpxwD29fbeat+7P3t73908jh9S26mfuvr6PlikHb+eqbK3971Pjrl0LADGA+0fGbmv8H0qmsOmvF3pPKMMz+v5R0but7b+rjjq7aaOGNutdk+2zeSlDMblbGvjQiv/nqK2zrFp02+sL95lZbAwM5ewLfojV2+3Sfurgu3v7bu3GweMNxjxWTcE2732HSdH1xlpL/MHH26Zcbdt0MdvioGBj9l3+AHfItrwQbW/+Rzja5YRn7FmINbwHSJ/OseJ2H12XbD5YBM7Z2/ve4ppWQb3n7lgO8fI2SsTkMlIgE4XJv6/0oL4B4qcdfT1MckvNTLpOdOq7hjkuKopGqoLZg4bN/7C2sEOW/nBCRds2A8RUgQS2hCBw+vq77+jFKjbgV3E/n7O5mcX37TgdSDYYtGgzdSzsikEU2za9LB9jy0ISNItLY5MHCMjP7D8CER2PnwBre801uvzPqj7HKHSic8D7LwMDNxheakf37JYhrgoj5ORkQeKXA7Px47PXU0hNB58AZ1tZAzF4lmtZ/JkLiCcOrElgG/7+t5r+WMXJnxbHd+ramOMPuntXdkcV+3gY4l+o83h28m01+epi0sWT/x4rdnOCVu5X8YDJ3P9/X9n+avjqTv9MDa9HSkGBj5k311kZPcZgUD78FMu/9hML+uNjHzPviNuMKeJf9EH2DAdbd0azPn3H+07/HC1kT4PQVzNx3fMS/xEPCBtOi+6N1fFrUEJtq3OoaFvF9OyjMHBD9vxvzZeYGR3ClGQnmGmZBIuMeH0qyJ3GcPDX7bj7NJdY2ShaCcYWkx3YzoBryUYHv5W8cnhgg0R1V6wIdbSHZ3xwGI1NFR/TYLX006wVQXUb+x7fPEOI0Ftodk/9ruy2mFw8FOWn91LFhS/XDV+fSxoLNxp8FxV2gGaKIaGvmpl4N+qsIg6coLtI1bnT4pPnWF0lBMJFmXaGjuGaT2TI2It3eGaCBB4/f2IBsZ2nNRUBUxdsPX2zrU6/0/xKQ+feyyUMaamIhjIg134jEUUH+LLq82Wm6x/vtMc353ARdv7LW9cnmdMUXZdqPp3HGNM8DfS5doQbYs81fR+LEVLsMVJIW0LUUGdtJe/UX9aVsryfVjsQPrOHZf2mD+pQM2VVbW5yrBhLDuiDNJgdzCXr+q7KtPy0vpz5UWZfC5fQSjvYBJn8EGsBWl+iG8YC8wDxkV6EhdtHMvOsGsybU/LSRm28f8oK2WkaVeu6JRg2+pMA1SAhwV6es4wnmkkELK1zbY2k4fBnStruS3a+beqb978iB3nsiiiiYVn7DPg6o5UAFE2OvrD5sLCrgCfx8KmTb+w8rikmxdsXPrKiTUWow0bftSsZ3T0XrO/7qMqvB7YiWD7lX3P4tIKgH19w5bus8Y7jPV32w0M/K3xfcb3G//O+CFjeu/OtUa/TFW/NJzWx4IWiw4Bysnlzxw2b36s6YORkY1Nbtz4UNtFfWjoS1YW7YnLZfQxPqBf64ItV87GjT+zdPc062rn94EB7q1stbcVcOtjqROOJdY2bfr1k21nPODLHFzADFt5CCAWKhY07IpFoC7Y8G2KaDtjPMZ2q3/xa5Qb/VZvy/iMvNjGGGA+4EfKv8p8cWOzne36OAVp+vq4VBKirSxU05MhRK1f1mbxTtOV25GeNIyO/sS+Iy2MseRMkQo2Thw2bXqkOOIgxvktDcQd6o845vVP5ISNEysfc/SD29Xf/8niaNjsbRwa+lbpRAw7+vrYmUxt4OrEP9rJ5r3N8ZHu7vL/sL239+ZavqrvUjKmo8wUcYuBX86Pvii3oRNs2PCQ5Sv7c+PG1gu72/u7bCdjZHT0p812psBvbAB429db2patubZTTiAdN319f9/8nN7aEbfTcFVovHLFlBJsW5UEihw2bNhkxxFrZxtZ6GOxKAe6MpfbxLqlKKGO/n4mHWeq3JCa7hRU7VplE6p+SW54+F/sGDtYiCLs8p2z4eGvWmDLLy4u2N7cTJcTbLkdJYRaby9n09RDXhd8iCReBtwOrbRclhlPsLHzd77xbUbqYqeD9CwE2HhNkbKFnp7TjVyipl9oOwKY/PiUOmP3bEFGsKX1xb2IrYWfwF4FYqKvjzTcm0e73N9xTyB+r8IXcPowRBt9TCCknpUmBO4vUtaxceNm8zv5sJO2eT1DQ6NFihZI621GtOE7Ai7jsjqWOuGq0kIT8HGAr2hzuf18v2FDvS0ITN/tDNEW88XrqS6eAfw2MICYYTeb9nvbvX76jN2NOGliEZzqwuL94bbhO8rEXsYePo0dt42Fhe3hJwPMrbjdgT6PcV8+8fJL4LSBuqiT+knbsi31EcLL00PmbWthTYFg6+9/V00AV8GlZy5B+5hhrnl5E4X3L3ON9rKj3ZpvbvNsGx/59975ZX38PNdsWW/pflYcGRvceuC3Y+ALYkWcEJT9R99ydaITETo6+oClp7x51obPFt92Br/NIr0VY4l9l+5O8sCGt9P7mrng8QY7EZQbM/MuB4Tr4OAXLB872NF2yqPtXl4aY2PcjIzkf7knhT9IE+Wm8crLFVN2XbCFo8XxyYMC9YUaDAxwTw7CgAUqdowITkwSBjSBokqOcVn0l0UpZYyOcj8ICzFPDTFB0p2Rll2Dg18rcrQwNPR5O0ZeFk4Ws1SoXGaB7H3ZYO2CLQQO7YiHAVZYwHh3kaoFFmlfMKMeFtBWPSxi7DDl0BK4pCWg4y/3TV6wRflc7kqDMAHuhiJlC77jySVq2hL36+BLFnJEMMGxvoCAfH2+8OOHanBnV8l9TP9XhSF+ZIG+zPqlvhPqPiQNCz9tiYVlRVvB5pfM8XlaFztL1Hep5avfHO+X2LEDX8diXh5LnbDaNwCh4r6i/YwH6kI0Rfvhpc22VuFjlcuYYVcImBXm1/yOYX8/L6VM209dsSOKAETUxxzEn5Q38bbm6bb5/KVs6mB++o5bfz+7j2PvMPsOF20OG4kRy2u+5RK4n1hQdgjtdIEsX5L0S/mMb8j4dmGAvSmGhzc0RW8n4BJ0by9jn/Lon8U2p39tdT3SZLrDxQkaMcT5S+OvkvGNTbR3rrWrdVKBkNmw4cfFpzpGRr5redjJXNLc6amCNjvrP9pPG3lYJOptCYzWWJjorSTDw+yEXW8nWu+1OvHBw02m4ApJ1Q/Dw3dbvrgVwwVPWbBxby3jlnlAX7cE+mRvPxgaIk5Eefgh1iLmcSqa6YPOb7UYGPiolUG51ROJGJeiU4JtK3JldicLbNr0c2NMToIZAYSJ7EFtLHImmAPBzxelVNC0JlyQ4JnCz+ARQkEWNAImwYCzegLGtRYEuB+oLNpoRzvBNjz8gyKVw4NhurPGgs2iicChjuA1FgweLHK14IIK+8gT7aNt7QRbiCFEFwIKu2LRnF+kbMFtoi20n0CJIOIsn7wEmljMlpWCF8jX54JtbD/QHvxAn4UfaBsLBr6fWVucyO8iJ+57RIj6Ap4TbEND/2zH2Dnk9THYiBglLwti9O2iInUL7Hi2nl4mgE9OyOTHG20PhjCkHtoc7ce2GTauy5fl/alo8uCv9MQkL9i8/W8yxutzEGv0EcKGuvBhulMRwrSbCwplYSP9xBjCZnxKvfm5lcLbjMhm3DAmYxxWBVt68zplh+Bo2VEWbJw4MG8h/g7B2n5XDLHNCRxjtrd3lvn3C80xmcLvTcPW2CHCry5UiXWBkRHEDHMOMjbp17hEnRdsqeDDZ97my0wQMdf+xf7Szivs+48VqfwS3dDQBrMXGxj7zDc/QazGGred+R+XofGHC4yqv7GFByf6+jjOuLrY0vxvK7N1ouECMuY24xWfvLM46hgYuM2+wwfEIOY2ZdEnjNPIVxVsnKATC/FTiGOfB1WxhogeHPxnay91U/bbm3bmTo4HBri3mhNUxhnj1OdDNeYF6PuhoS82fYlP+/vfWyvX53y0hfFQHZeiU4Jtq3Gi9yx0A4ODnGET2FmMEA1MNiZxy6404IGhoTvtewIFARPxQLBkYhEECHAELSbZjTZpW0EQIDp9IawLtupC7WfOCBTSImwImgQG8lBHkIlfDmjAAxr5U0HqAaozwRZnjL5TWUVLSIb/IgiSj6AduxXsbHQu2KoiouWH8Dd+QxyGH2gXIoz/z7FxVH9p8sAA94awsOG/6Gd/dUUKX+jxG2I3xAqLB/7Dz9RB385pBvUULthYPGhPBG9fuNLxNDbLl9ZAa7xhDwt0XOKkDtoe7ceu2bYIlx90Ae47/BbjwPul6mtvf+yckifajxBgEYy66Oe0j7sp1qoM8ZbuuN1ki/7NNeGTwv0Vt09g75LaOPTLvgjy8A1jkHqi3qpgYyGlDyACK8RVXbBhW3//WjsW45YTG8/L5dLUdv7f24uPw9et/qwLNuJHTrAxB+uCLcCuZG8vYxO/ME6xifwudvr61jdPbv0SKT4jLceY3/iI/+PPS5p+CPhl9zhpo/50fJVFtQtXysIG5n7YcFHTJ5Tlt5rQpvAF/XJdUYLDBRt+IC7kBBtzfF6p71xYRryOy+Xc51x+yI2dMK+fNoWv+D92X2zpq7GTMUH6WEN83g8MfK5I0QI7g319HKftUa63P/Up6OtjHKY74y4E6/NjZ2bXBZtPenF8ciPmdMPvjWPixOWT8o5BTkT6fTwsaky6EAEs5BHsg9xs/+kil8MFG4svYocAE8F5eU0YDg5+3L6nHgIzwYIFgoDA5E3rod52O2AENIJsnP2OJaBCGBJ4yzsx5KnC01fLxx7qiHzOzuur1+OLKgtU+JvAyGJG+vABdfKXvptb21X1hY5gHf3sYqMq2FoLIiSQpgsoeaIO7o8p30g+MvIt+55+ze3Y1sd7nXUhDdxPtB/7GTP4OrUn2o9diy3Q/22RswUeDGmNIYQeZ+xLrQ1lwebpqAumi3AItLS+tJ9z7ekmqSP6GDto/yzz+fcLy+vo719naejDEFb1h198bJEmhB1jKua/t60u2OgHyNhg3Pp8TOFijfoZRyz6+J5xgaAg3zVme/k9kYODn7Dv04Wf+YToaF0OHBn5tn0X8w67Y+eXMcEJE3m4Z7Qs2LDHX2VETGAeIcLCHvJzAkQ/0x7KYfzyPeUzBrA50s2s+b0ljklDGUus/R8vjjp8h4sxBfEfbaX8KJu/1BWM2yoYr+XXFg0M8DANfqBeyqGPow34jrYuLPWd31ZA25lD9DVjYllzNzFA3OjtxX7sCzFFu1IfXG3llk+u+/t5fyPlYgP1c3JQ7gMXzIhFYgR2MCbIQ9nXNHf0Uvh4oJ+okzKJ89M137YXSrBtJa6oCZbpAE+f9vYyETlDI0Aw0VnMfFJUF1AuN7mAqi5oBPrIF4sZ7x8r3zjrgo1gS7AJweYLexV9fUxQ6kFQVhfqqMPr4bsqvJ5uCbbcLx3EwtFOsLX6trP6Fljg+0SRogXvHxa+nL+jrtTvBOqqmEKIUReLFLZ6/rxgi/6JtAR26qJtUc+yTB0Itpw/Ul+Mxfplcd+9wJbYyQzBxRig36PtLbvwYxUuxFiEUsFavikbeDrawKJCO2K3Im1/lbm2bElSp/dzTpwGfBeGBZ02s/DPt+/Kux6+K8q4YtHvVLAxHyFix8ctvkkxOMgTj/gx5i++pO/wPbbMNtv/pkjtGB3lHivSMsZDfC0ujTOelvU0tCuER9hAvKCf6i/s9l93YQxhD+OAvLErTn7qIg4RX+hvvwzpafhLuhBC7OCVT0R9vISApI2LzNbyT475ZVDGMvUzlpnXpGU8M8f4y2fqIxbzf77HroVFKY7WbnZ6EkIb8EHMjepDBwg2/Ma8RlgN1kTl8PDX7XvaQXsYF/Qbggl/hJ9usv4trwvDw7ywu9z+auz3eM7ONeMC27Ej2knZ5fuEXZwTsyiT+vE9435rzLltlRJsW4ErbALUb+yfLgwNfcZsIIgQQAhKIVTq2+UuNJjMBL8QeeQhQDCZyu3KCxXyE7hago1HvavwNARYAkEEpVg4y/VQdxWevyogsHFLCrZcQOlcsFXTgby/8UHV38Gltvg9WOR2uFBGaLNQhDBfbEExJ9jiEhbjgQWjembr/88LNuyMxR9/TEywVe1pjRcYArKdn70Mxkj11yBagjX6ygVrXbDFzgULSgiSdBxU69saDFuYC+WFPIULNtrSmmfTJdi8XOqGlB2LPuKD9NQzWDpJ9b5m7MXJGWOPXdBUsCE6sJf6QxwwHlyo+Xir3zPaijmQMcAccBHrtiBygtiHnSGimG/UEbbjx6pgo1ziFLazO1fe3eLeOT9OOuYgcz7GcohN/rog9DpdqPmx8i0ZrSeYKQtRSZ7ou4gN5R3knGAbHi7vFPb3v9u+p9zYuYt+S/2EnXOLHA6e0PZ85KFsTg4+Uxx1+PzjxJO+ow+wm/ETts8tjQcX5yHMJ7NjvzOw64ItgovYnsttwOffuTU4yA2yf2V8o5EbwTlD4TIhQmZi5Ifjc+B7DyStwB6BL7+AIlJCQMQWeASKcrvaC7ZYgJmInLHW73fwNExwghKBg8md2+lgEo8l2KoCot1DAKQnQLAQEKgJTF72xMqPoNKyr7P66jsgoOXvCIa+kNXrCXKps3x274KN+ljs8KUHyfaCjXSIZNKxYKR1uT/ygo3+qo6LdnZWWX8Iov2ObM7Pwdzl2m/Y9/g6bPNFMi/YcoK10zZMJ/FB+1/k4B2BrXHjAmigcpnKhRVtTf3CHKP8ej/7uGXhjRMNH7dVO7xc/M3iHDtmnq7Vd/g/LRsxSF9jS8z3nOgIwYZgrM5Ttzsv2LCHtkY+7Albgu5TfMB70YaHv9c8+cEGpz/IVf0lDC8/FSwLmukCLaHLOEasxPyIeFav38n/3WcpXLDhh1y/BXO+Y2yHYOU1G+U40epbGDtbzLe03/jLSVHLB61xEfNmjtlYFbW0n/6N3UXGhItRLze3m5r6a7y4tzNSgm3a2dtbvjQQ8JflItZ43xcLYSyknKkx6CfG6s2iKfr6WJhJx0QOYVS/x8knJpMOMpHiLDEmc9q2bgi2ToQKn3d0wRb+dn/l6wkus0Wm/KSo/6wZ9aVCZEGtf12wYROXWjgDZlHjrDot3/2RBldQFmyxEziRADuWYGPsc/9LLPxuQ76cpbUdNn/ykzJijFNGO8FG+5ljiAYWq2r7txXS/m1ZsLFAx+44Y4FdlOg3WF6gW4KNPmrtqHdHsDH2ycO4jhOWEOKtfHBw8Ku18TMe3M+UH34s31PrbcNnjMHYMcKGdH6ELR6jWnPc/5+iO4Jtdu1BLz9OOyjbhVe538LO8i0R9XExy2ws/yyhjzP6gfGYrjPRzvKJVl2wTTSe7AyUYJt28vbtHPyBAHbWWASZCAx0JhEBhwE/UV5jIjD/VNnwMG/EZ0IRBDmr8jOfauAjf1lAdEew5RYef7EvgTCCkgRbp4KtKkRciFHf9ijYGCssJPgJwVZdoKusjyW/PDhRwUb7t23BVh1XKXxHfmsJtlRQhL/HFhQtwcbYiziEqOuWYCNfzNWcwFnR9krHeCg/Ve3tTdHyW8z3Tk48ghzfMoKtOv7dT/g2nSe58c+4qPYd7aN8TqxuMBurgg17OZ4K1jSO5ezFnrBXgq1OCbZpZ/UsJzA4yM/9xI+9MzE56ySIEaQYvBPlLAtIPy1KL2PzZt6SHZOZgOYTNbcg+KPxnQiIqQm2wUFenpheYtvxBVtv761FihZcRExMsFVfAOr3KVIfizPjaNsUbOxuVDFRwdbXV3+tSV8ftlBGp4JtrPZPhWG3j0P3T/Rlvj3tuaytwPD5zM484ybdyd4ago1ySTMRwUbZ3RRs9D35Ir7VBc7g4IYitYP7qYaHv2FlEYeZ45D2+DvJUtQF27zMJUOOx3zv5MQjyPEtI9iqO/E+1zoTbOkupPcd+Sh/LMFG+9N70tI4Np69E40nOwO7LthiQIo55m62B345lJd3EnQJqAQw7t9hYsZ1/4lyoQWlLxU11OHvTGJSxSUMDwJV1IVUTKR04YHLaguwBy6CMoGBiehn/tRTFQCjo9+377n/jgDOriLBmeARk7ZVT07oeB2xw0CQDsHHU2Tlnaz8Tg7BKhbWcsAE7cuv+6Gz+ghg9bet+y9SpDuN7fzt7O8vv/sOuGBBsMWlvhBs5XtYWoItvSSYXjqC7o+8YKO/CPaIneolj/G4LCu2fLzhq7LAb1cu9x2l8BdEp+9VCwGRE2w8JTpe+yfLZU0RQJ3+u5GUC2NMd+onZ85XgeHhuywNsSP85jfn1wUb7+djoQ2hEQs0ddT7OS88fNymKAvBarnBJU1/BPznzRjn+J6ysbn8xHNZsPmlt/I8dbur883HflWwle0p/7Zl+noL6qK9/KWMC638nGBjfMXYn1uy25925njqt6rd7cjxqiDuzL91AYQfiFfYyE+dVZ9kpRzEeLSDvq2WC8vx0C9fko82uiDjZ89SuL1xPK7MpON+PHsnGk92BkqwTSOXWWAtv8YgsGEDv/sW967F5AnBEoN2oiTvwlKQTOHCgIDCGRJnt0yoxaUzReD3Q+UWZiZfq308Ml6tq3VPEgtJKtjqTzb6QksgJEhyNk2Qow3lergHMHfPidez/Qk2fsQ5hb9UlDRj+ztY3bH1xSIEC2UQ4KmLhw62LcFGm6qC1X3ViZ99LNQFL8Kf9tOudMGeXsFWHQP8rmJvL8fwk/dHq1/dx7ly+J4TlHb3WfmrejjJoS/SnbB5NTHvr99AiKTjIhZot2Eygm1w8GP2HQt0jAViSdmPVVt80aefsT0uidJHOcEW7coJn8kJthT+zjRsp53RDoQvdl1t5Y8UKR0ep1OhM9fGXfln0lq/g+s7UO63dv2cfsf/2wm2XL8Fxxdsg4NfKY46/PUntCPGf73fsKe6G+nvzCRfjAtemp67h02CrbuUYJtGLmsbdP3pUBYZBmxnOwvjk7xLaoEk8PDDv7Xj6cLIBFlsorL8gkvg9wQxAQma2BYB0INLTqwBX3wJboipEGzerv7+jxapWvCn+wgE+ACbCEwEEK9nrIXL69lygs0XuxDUBE33l9fRygc7F2zYVn6BJHCRjL9JG/7GD2ldS7P3Q/Jj7S58WZjxIz73/NuiYONHqqvwS7rYxP13LOTxioFou+fN/XC37xpgV/jPd27IvzUFG0CM8xLWvr53WZrY1a6OobQcH0tVUZpiZIR3afGwEnMs2sHYp+yysPLXMYRgo8/S9i6rjadOBRvt8peppvXj81Z7qn3l6UOw0c+UXX4wgZ8w8n4kJuTmactHKcYXbOX5PTj4SfsOvzBHaQN1McepD6FzV5HS4elIHzte82ppWi/9HS+eR1tSlgXb8PBX7Tv8MDXB1tt7c3HU4SfJ9C2+Sh8WwYaWfWm5fkJJH9Mn+MBPECTYpoNdF2wx4MQqc5eugF8O/UtjeoYcgYkBngbziZB8PK5+e1FTHYOD/C5c7GixMC6wyThUE1/Y6Gd5MZkIyNjHu73KIiCFCxXEQ1VIMRHrL3wFHpxisfadAurh7LDdbiHwehBUcRmM4EM99bdwu10scHEGTNupJ/zNk4flnUZfvOgjbPP7C/v6uMTEguf1hM87r488/AZg+ceeAT+b1NfHJCU4Erzc37C395as31uXoPEFAZOxFIKlnWDDpgjYBNUI2Ok44n6TdoItdwk7zd+O7qve3jXZfmXB898fZIEKAUL5S8wvH8zeC+o2MdYYB9hFm5hL9FE7wTZe+yfH6hioYuPGn9tY/7al+6S1k5+doW76mPfzfbZ54pSbHyn83rW4lYLYweIYJzq0o/w6BhdWt9j3jI24J8zn18jIpiJVCz6eWETTcYud9RdXt8qOBZr5h995qWrZF/5CboQCY5X52ho/aZs9HaKA+uPkI8r1sQCr5bvNtJGY07ok3uqfsiDasOEB+w57EGKIIsYCIouXzd5eG58+xvB3CF98Un7PnPuDX38gDe1jHPo89DH8d83xyJWG6Pe0XSlcaFNfKqzIk8ad3O5kCKDw7yIra3ORwuFl499qv7kd1fve/CevKBd7IhbmXusRgi1OviPuR3zI3a9YtXci8WRnoATbtLE68AP+dCiCjeAVi1+coU5lsJIXzrfAl/9BeK87nVQEgfk2eeq7HoDLbfzEDLsEPNBQDWT83mT6I9X+4+/tBBuBvPyyxQBnfqOjP2zWMzp6v30u7zBQ78aN5TN236HsnmCrXrIF2IWQIGjFbx5yZu1tikWyvkCNXR9vsL+t5ssAPwuDH0ZGfmD8obX7l9m0LBB9fZRJPSw8+DvdCayL660v2OCC2u5EgDbRz97+e40/rNkR8EvB9H/sZMYCFONtegVbb+/6opYtA8Raby8LZvxwf12g0u7h4XuKHA586pcw3T/4vuqXQH7c5gVbgIW3rw+hcoPZN2SfN9XGq9dPmSzQsQvm87UqHBFT/usfl1h/fczaw8KOuKGffFxX59vYgi0/nv1EMezhB/dX1mwJ5AXbXEtfjpv4mku/fX2r7Tht5L7Cz1ibWrELO3zupDGkLFyB23e+2TVo/vuC8Yv2mTZFX3cm2HKxBmHuu4yMH798Ozj4Zfu+PC4Q0L29tIP2I6QjxuReLizB1n1KsE0b213WGBh4rx3nLDkd3NUzwsmSwb7QxEf+sqjf/8KZdioUPWi0e8K0HRAWvb3XNyd/wAUbQion2DzIDA1N7FcfCBr9/e9pBsIUrXsAuyPY+vqGa4EtB8SEt4uFkrbxuo52P9GVqw8/LLQ2/UMzwE8GCEl/LQq+jss1XNaJBdb9sG0JNkhaxvk8Gwf1J0Y7BWPOx3HcVpDu0DKXqKd8CQZsScGGL4aGvl7U1F24WGM+ETcYVyyOcfmXMUg/+OLY27vWxkf+hK0KTrg2bGidqPi4Ze6m47Yu2BgLnWLDhh9ZfvqIHS3sZhe4NR/YtR4P3s4QOfX55uW3E2yQWxHqJ4vMP56ArP52ZjUO+Eko9qeCjTp4gW59t3wsjI5y+wPzh5ML2oQfGDt3FynyoB6POcQ58vA7rOMJNsbF/HHLzgHf8IP1Hlsol7bHDj67wtVfOpBg6z4l2KaFuftZgN9Hlj4dyqITl7AY3PnyJkZ+IPv9RY11+KLF2aLfi9BatHgMvPwaiBz8LJLJxsJ9gU3CVLAR8GPXI+5hi4kLmZCDFkA2dCRWCPa9vZTxNquzKtioh8UrgvR4gi0WjRA2qWDDb4jJ8QPbwAD3H7KYEbh9QcsLtnb1hR/mWNsWlxbMTsBvMvoOBOXjZ8QHuyf4AF/Tl15PXrBhEwKHIDlRwYbPY9Fqf0/f2KT91HmTLQhcJsq/9iYHxszw8AbLS7tpP2QcMpYZJ/iYhdrbXxds1Rfndlew+UL2iQm1aTz4PWvsyLOzhmBmAY3+Dvu9z5ycDNw+rmhjJ7O398bSvGrN37EFG/OO+w45ARwLo6P3WlrKih0qTq4YO+k4XWTp2s8B+tzjJDs7xMrZ5uOqWGAcjC3YqK+T+e0niOXfcPV4TR0x9hlnfkmTnbkNG/K/MlMFcx2fux9oE8KGuIWtc01Al2/LSEF/+UkGeYjbc0pztL0Aws+I3E8029YJGL99ffiM8ug/+i7GnM97Cbbp4NQEG4nJRGYKMcGGc8UqueemOvnYFRka+pQd52wNoRHBi4HKhI3BOlX6wjE6+oAFu/KZIoLRL6MxAdMdGern+1l2fJ3l/aHZX17sCOb8CHDrPW2+aHIJI+D3R8RiysRlESUgYZOLKQ+miJWFVt7dVm5L8IHNmx+x+r9ndpCuVc/QUEsE+82zfA8jSLcuBfJahbTtbhc2sVinC1HYhN/wwXyr912W/sel9rMw0f7W+87SRRPh8ZEJ1hd+wOZ3WJ1cjvlOs46qkKWt3N/mvqfPWFBh2IGfWcwYRwTnGEdLzN5vFqU43P5UsKQLZ9DtSx9GwabyQxjpuA3/dUrSY6OPNxYhXqOAEKX9VTAe8KfbHm2HLA6IVfzLAoEvy+1PL0XRBn+1zXjtnyypl7Lwy0xr0z9Z/a25MREw3rh9oa8P/yAWiBmMdRZFxh39zbG4DyrtA2yYZ2MFwf7dyjj+z6ZNAwP/YGkQuhfZ/1uvHvKHX/Ar9SCCqcMFW4xvFnP34Vubc5S+YYwGEAWcaA0MfKhIR6wJsUbs4F4x+j78jv1cJv98U5Sk8Et3n7Dj5GXse7v7+z9cpPD6vB7aE2KB8ik3fNLyCz9KPzr6rzW/8MDD0NAXLA11XfzkcY75eGOuEWuwAZ/EPZaMIV5z8ZFmu+tx81fNeNrXxwLMuGP+UAcnXfgiBJvHxeHhb1kZrdtM3LbN1mZ+B5T2IdrId5N9/6siFXP78/YdfuBEGRsjHlJ2jMtrLd0Xm+WlfQaw2/uNscG8or0xVyiT+dIaD8S8gPcB6ehn5mOcqFN/jM3FHdo70XiyI3Pygm0PowRbR2TAQQY2CzWBjwDIAkvg5S+fCUCcMfoE6N5ApRwmKYGA4EWAZ2IgfiLwMxmr9ROA+D/fERQIDkxcJiFBHFIOn7GfAEkAo3zKYuL5IuAkOOeESgQnjrHwk5/Jjk3VeviOYwQ47CEYpPVwDP/6DcPejqAHUreNdpCWYEnbCA7YkPqcPAQ2jiHEqCvaT5+FXXxHObH44Gfy8beT+qp+IAgSsMhHevJSTzviE9Lge/L4IlYfR/zlM3YRQGkP/UYd6cIWC2dK8mIbdhOo8T/tIX8EZMpN65sIyUO9Md6og3LpU+rItRvG2MMWxkHsUmAnbelW+yfDqI8y6Q/Gts8hxC67mwhSTpqq4DtuJ2A3rfX7wrETH+IUu+lvxiZton9y/ue76jgOn/rJjzP1JWXzN8YWnxm3LPLhV+YTfcV8Iw0kP39jbFAm9UQdMHyezhfGPmWGvXwOe4kH2BH20nbKZbyHyMEmbKNfY77FfOA7fEOZOb+4oHa/kC/md4wvSP3BaBNjE9vScYPviZv4hnrxDXOFPNgdPojYAfEVtuLfiI9hG3bTPnxFOaQnP36gTOzFbvwUc570+IX5kB6P+RmM+Rxtpz2UX7UzGPXRZuYntqbt5i+fY42JGIEPcutatJFyxrK3Op53ZqKxpibYDjGGYHttvhLRB11MkAiaITT4S2BhoEfgJX23BirlMPAjqDFBmVAECernb0wS7EvrJ8gx0QgGHGfyhd1MRiYYwTeCIxOZdExQ6iHQkCcWlmr5Vfs4jh/Ih42UTV3Uw1+CALYS3Cif4JTWwzE+Yy/lUW6Qz7FwUjZpw+8EWAJt2JTahb30C+mog0UXW8IHtJ3yKDeCZuq3ydZH2/AneagDX+CHIPXzXYwf6sHv5KVsbMiVj10EScqmLeSNxSLyRZ40L8GVvLEQ0R7yR/DmGOWndU6EYV+MA+rBLuqh32McVNuPb+l/xlf4H1urtkyl/ZMh9cFYyLANG7GVerE9FSKcQHGpsMrYVSZdiB3ajM2MkZhT1f5O7Qi/+q5Ka34xroJ8xhcsnviGv/QzaSH9EeOW8qgz5ivpgqQlL2VRJuOT8vkbY5XysT3iXdpXOXspN+ylDPxHHdiEDdiEbZE++pT/812Mh078wngLWyH1xtzFjmgXaWPOp/ONv3zGrpjDMVdSf0fZUU6IGvKGbdgdsYD2pP6MsRvxLvom5g71Ym8cT+cnpGx8T9vpw5hrOTshx7AVP1XnGf6MdnOM9lAe9VN2jNGom/TkIw/tG8/etN92ZnZHsP2B8Y+Nr7EO+/dWp4gtMvAYzAxCBiODmIHJIGUCpIE3JkGunMmS8ig3ghMTJOrnL/bEJMFO0gfDbvJhJ/aSjwkJowzKZNEjHZOQ8kjP97nyU9uiHuzDDwSvtB6CM38JBJTF8Vw95MGGdGFJy+d7jpOOciDlhN9Tn4Vtqd9y7cemtF7KIhDxd7L1cTzalvZV+CL8wXeUTRrSpvVTVrVsmLOLdlEfPiJvmi8YdsWCQL5qu6OOXP7xGHmr44B6YgGItlfbj/34lfG1pdo/WVJnOh7oJ+rEdhbcEG9xAoQoC/KZ7zlOOhY08uF/2ouf0nGeqx+GDaSlnbQ9/ApTP3IM32Mn/od8X41P0U8xLyIt+WNOUmaM3ZgnfB99RVnt+iqdBzEOohzKrJZDWv4fc4Y86fGcf6r1YHvMt/AL/48xEr6I8mPORTuiTFj1D22nvCDl8h3l4NvUH9Vy0nET/oz82Mxx6iI/5VBetCVspI1RZpSfjsucnRHfqCvKwk/kqfqUsvgubKVd5KHcdJxG+qifY53YK5rGem2htdBcaK/9jGixjgQbiX/feJTxFcbTzPEP5isSfXAyaJlQDHoGMoOTwZpOuC01QGNCUQ/1Uy/1Y0cEDOwjXZovJhZ5mUTkx15IOfwlL8fIT7poa6SHuUlerQeShry5eiDft6sn7IhjUSZM20A6GGVF2nZ2pXlzdvFdtd6p1JfLH/WlbFd3rlyYK5f8ndrFcdJFHvJ3WnenpIxqXam/07ZH+0m3pds/WUZ7qJM6qBP7mXuxQIY4aCdKU7FDPvJj80T8Hm2PdlMGcz8YcSj6lL/h4/BzWh9/q/1DHhjfUWbEubSOTvyd2kueqr3VcsK/fBfjI45TVif1tPNLlBc+ST/n2hFlhj2kTX1R9Qd1j1dO2EaeNH/YEH0TdUZ6/lI+x9OyJ2InTMuq2lkti3Thp+gDjqXpIw92dWrvzky0FZtiTa3VkWCDTzPuZnymcV/j84wvNB5v/NOenoFP5CsTnQzAGNhVxrFcvm5xsvWneSIwVhkBI62D74Lj1QGreaPsCGjj1VM9Xi07LTfypGWl6VNG3jR/ylw5kWey9VXzp8z5I8rNlZeyWm7VrlyeYJo3zd9p3Z2Ssqp2QtodjO/S+juxoVouf7dEG3IMG9P6Y6GMBa7KOBYL31RtTW2oMo7l0sR37cqK/6dM8wfjWFrOWJxIWWna+H96fCymeXNMy6t+hmOVCavlBcfKHxyrjGr++Bzp089pmSnTNNXyU3ZazmTyRL70cy79zsqZd5vGOtX48kJzsVmGBkOLocnQZm0F2zOM+xifazzC+DLjKT09/3Nh2eFinelgrjKXvtvM1RvMpRdFsXtM51uItlSIQsRZ9btUrE11rqY2VDlWmrSMsdKNx1w5YzFXRnC8tNXjY7GatxPmyqkyly9lLk+VuXzBTtJW0+SYy1dlLl/K6cqzsxFt1fNq4x8ZjzSivdBg4wq2XY0Itr2NBxsPN77EeJLxL+xs8Df5CkVRFEVRFMXOOf9xk1pnmL462fhS4wuMzzEi2NBi4wq23Y3PNh5oPMx4nPGVxv/W0/Omm/OViqIoiqIoip3z/H9ybdVzYqG10FwHGdFgaDE0GdosdFoT/AcFt4uRm9z2NMaTovzaQfHgQc9f9fTc+NN8xaIoiqIoiuL4REsd+FbTVfHAAVqLV3rwS1N7GdFiaLInd9cCIdh4GoEtON7/wU1vXEvlmipbdVwW/fOenhde3tMz74n8tWlRFEVRFEWxPdFQp8w3TfUXxrgcygMHaC6eEEWDocXGFWxswXGzG1tybM0933iMkZe6oQT/0sqelTdCFEVRFEVRzBOx9mdrTEv9lZH3r/2J8VgjWgvNxTMEaDC0GJoMfVYSbIAvuFaKouPaKZdF431s6S7bG4yn9/S8ZLCn5/qH8gaJoiiKoiiKLaKZ0E49f238cyO7a7yJg921eP8a2gsNhhaL+9dqSHfZ2IpD4cXTooca4142Hj9lG48nG87r6XnT7f5IuiiKoiiKoljm3CdcK+0zUGin/278UyO/bsAVTB42QGuhudIX5o4r2NKnRbmOiuLjuiqPm/IUA5dGqQjRdrrxHOPbe3pOfU9Pz8Xf6OmZ9WjeYFEURVEUxR2dc/+jp+e6n/f0XP49k0ofNB12temkc43srCHWeFEuWuoPjbzvlh8q4EHP2F2Lp0Nr96+lqO6y8R4Q7mWLJ0a5NEoFIdq4PPpG41nG84wXGy8zXmHEwGuM7yg4UxRFcSfitRNgLr8oitsHQ+egedA+aCC0EJoIbfRmI1qJy6CINe5be7ExLoXyZGjcu5Y+bNCRYIt72eK3RSmI97Kloo3Lo9zTxk1z7LZhzJnGs40oyfONbzNeaLzIiOGiKIqiKIo7EtE4EM1zgREN9BYjmghtxK7a64zcs8ZlUDQUYo3XeMSDBlzRjFd5jLu7BjiY7rLFpdFUtPEQApdHue7KzXIoRYzgCVJ23P6H8S+NbzL2G9kChFy3xXhRFEVRFMUdgWgbiM7hNjG0DxoILYQmYlPrFCM/QMDPT6GduAyKlkJT8asGiLW4FIr2CrE2pmADIdiqoo0CEW1s3XG9lUdQjzJyXxvCDdXYZ8QwtvwQcCjKPzPyJl/4elEURVEUxR2EoW/QOmgetA8aCC30KiO3kCHU2FX7AyM/+ZkTa1wKjQcNxt1dSxHKLrfTxj1tPIjAEw1UinBja4+nSDGI138cb+SSKSIOY9mFgyhMURRFURTFHYGhb9A6aB60DxoILYQmQhuhkRBq3FaGduK5ALQUmirdWZuwWAuEaKOAEG1cX+WmOJ5kQBlSKZWz48arPzCIrT523o42Yijbf5AXw4miKIqiKO5IDJ2D5kH7oIG435/bx9BGbG6hlbhCiXbip6fQUl0Ra4HYZYudNm6Gi6dHUYZUymVSdtwwBIN4BQgCDiXJDXUYG+RdI6IoiqIoijsCU42D5kH7INDQQmgiLn2ikUKooZ3QUGipEGuhs2KjbNKIAigs3W2jMtRhiDd23djiQ8BhGL9FipGQnbiUiDtRFEVRFMXtkVVdE3oH7YMGQguhidBG3KcWO2rx2o7qrtqUxVogJ9qoMIQbl0oxBIMgAg4DMTSIshRFURRFUdyRmGodtA9EB6GH2NQKoRY7altMrKVIhVuIt1TApSIuhFyVGC6KoiiKorg9s6pvQvuEOIOhjVKRlgq1LYqoJBiVVwVclWG0KIqiKIrijsKc5gk9lBNpwWlFtfJgKuJSpg0QRVEURVHcnpnTOsGcPtpukDNeFEVRFEVxe6cgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCNsBenr+P/GJbf3IDe/dAAAAAElFTk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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={5:11:1};
b={5:11:1};
c={1:5};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b - pow(c,2);</text>
</varsglobal>
<answernumbering><text>abc</text>
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  </question>

<!-- question: 361117  -->
  <question type="formulas">
    <name>
      <text>L62 - d(a+b)2+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{d}({a} + {b})<sup>2&nbsp;</sup>+ {c}</h3>
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{d}(<span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{d}({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b}</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(152, 202, 62);">{d}({=pow(a+b,2)})</span><sup><span>&nbsp;</span></sup><span>+ {c}</span></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Multiply:<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><sup><span class="" style="color: rgb(51, 102, 255);"></span></sup></span></span><span class="" style="color: rgb(152, 202, 62);">{d}({=pow(a+b,2)})</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png?time=1624663720836" alt="Multiplication and Division" width="200" height="55" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{=d*pow(a+b,2)}</span><sup><span class="" style="color: rgb(204, 51, 255);">&nbsp;</span></sup><span class="" style="color: rgb(204, 51, 255);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(204, 51, 255);">{=d*pow(a+b,2)}</span><sup><span class="" style="color: rgb(204, 51, 255);">&nbsp;</span></sup><span class="" color:="" rgb(204,="" 51,="" 255);"="">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>d={1:11:1};
a={1:7:1};
b={1:7:1};
c={1:8:1};</text>
</varsrandom>
<varsglobal><text>d=4;
a=2;
b=5;
c=4;
ans = d*pow(a+b,2)+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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  </question>

<!-- question: 361110  -->
  <question type="formulas">
    <name>
      <text>L62- (a+b x d)3+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b} x {d})<sup>3&nbsp;</sup>+ {c}</h3>
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td width="25%">
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 51, 51);">{a} + </span>{b} x {d}</span>)<sup>3&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; Multiplication comes first.<br>
                <p><span>Multiply&nbsp;<span class="" style="color: rgb(255, 51, 102);">{b} x {d}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{a} + </span><span class="" style="color: rgb(51, 102, 255);">{=b*d}</span></span>)<sup>3&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>Now simplify the addition in the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(51, 102, 255);">{a} + {=d*b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b*d})</span><sup><span class="" style="color: rgb(51, 102, 255);">3</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b*d}</span><sup><span class="" style="color: rgb(51, 102, 255);">3</span></sup><span class="" style="color: rgb(51, 102, 255);">= {=a+b*d} x {=a+b*d} x&nbsp;{=a+b*d}</span></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,3)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,3)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
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xPO+2filBexvr1n27sttubjeeYELvCgvxNFuTnG5c2HnnkiSJVGWeddbOlRSwh7hZa+cuNa0r1dZdrGtdcUxVsvzIbLmxy992vMTvmGBdb2tXN9PlyOmFdsHk9F1g9V1kd+GeRpaOe1VkRfPXVH7O011q62YVN4Z+wK/5PGauMKwvy/zRdlWsmWZ+4Y9H79uabv1mMgDzWr/+8jYurjbNsXCyxPCuezJsvVxTFnZGmsbor2HbffcgCjzg5rml88IP5n6I6/PBLG7vu+hbj20y0zTBhMte42PKsaNx554NFqjLuvPP7RfprLO2gcYmlX92sJ1//VLnGRMkXitod9933S7PhvCZ32+1Ks+Em4yJLOxU7yFcXbF7POVbP5VbHLONCS0c9qxrf/e5vilQtnHnmeyztpcZrLe0849IivduVPjxx332P2nfLjKRZYVxlbNeG1ZOqT9wRSd8ua3tSFbjzzh82jjhigY2J2cYFlme5caVxWx4f2AV9jrWoMb31WO0PxpD6ZEehaazuCrbddhuyBUmcHNeURELgnnt+2nj6009v7LLLucZLTJRcZ1xo6ZcZVzfOOmukSFnGww//ztKfY7zc0s8q8qxq1pOvf6pc07jqqrpg22WX8wpeaTbcZFxkaVc30+fLGY/kqws2r6PaXupZZT66w/zRWjQ/97l7Ld3FRvw50zjP0i0p0rtdVey66xzjbON8O77UuPLJtGXSJxOvT9wRSd+uaMyf/5ViJLTHww//e2P9+q/Y2GCOMHYZY8zXbXOMPP64vyeSv2ed9XH7bnnBiDEa19PLNRZvWzv7H//4/fYdY4g+WWHckrFfnA6axuquYNt11yELNuJkeOaZnyqmWhnr1n3GBNsZxgtswb/CeKOlX2JcYVxjXFoSBynmzfuo5bvE8lxrnFvkWW3M2zA1rmlceWVdsD396ec1iWDbZRcXbG4DtufKGY/kqws2r8cF2y67uGDzelY1ucsuC4w3Gq+ydBcaLzbim5lGfINPw66cIJxhvMZIGQsszbIn05bt8zonVl+aX9yxuNK4rPG1r20uRtLYePjhx23Ob7AxMsfIGI65zjjeVsZLeX5ceeWnmmN6l13m2zHsDVtzeTtlzK2UuXQ7Ojvzw5VXlm9HYU0g3nqsYRwRrxRvtmeaxuquYHv609fYoiROhp/7XP2nqMBhh13eeOpTz2w87WkXGWdY2jnGZcaVxtXG5Y2PfSz/g/AbNtxned5mvMp4k6VdWuTL2zA1rm5ccUVZsG3a9Eur99yCVxQ2LDSuaqbPlzMeybe6qKEFr+OtxsuNN1qaBUbqCS42zrVj1xuvNl5jnGGcZd9jEz71svPlX2a8xPgOO04fUF6uHXyeaH1pfnHHImNhhXG+ibb8HM8B4faBD3yncfjhlLHIGHM3N+amkz5mU1xxxYiN6+uM19uxecblxqnEmZgXtDUY3+XS76js3A/V2Mv48bhPv8y2NMScGD/lvOL2QdNY3RVsT33qGhMX4sS5+slLDCk2bvxJ4ylPOct4tvFSS/dO4zzjCuMqI3lXNE466UNFjjIef/z/Ng49dEaSd6FxmXG1sWrDVLm6cfnldcH2lKec2+RTn3qF8SYjNmD7ZG0gX11QeT1vtWMI3BuNC4zUE3UtNy424j/smG2cYyQdPllp9LLz5V+QtGOWsV07ooxO60vzijse6WPGCWNhrp2Y5U+u2uHxx//LTsjutRM3xsv8ohzGVjpec/VuKXqdKS6//Hb77irjDCPjfKkR+3L5x+aGDa0nrNeu/aZ9t8RIm2PO4Mt83h2JDz/st8fQ/6efPmLf4Qf8St/n4s5Ki7ePNvOAD3zgmxavBux7+iTiYbpuiNsbTWN1V7D19FCoODGubgwO/ksxzcoYHLzdjp9lPNd4pfEm40LjKuNqI/n5//LG5s3/VuQqY2jos3b8QuMM4zzjEiN5I38njPTUtdK4ouDy5P8rGgMDny9qdSDY3HZ4hTFn/8TrgVV4HW81Xm680bjASDlRF/mWGRcZ8QOcb1xspHzqI53XW0Wr/MuM7zTONS41UiZlk28i9ZGu2v6UOV+Qr8q07siTKy9YLZO/af44Fsej3vh/mjZXfreYsyXX9qpN49mVlht5I38wrS+to5PycyQPZdH3s21ej9pC/J/FyOoM7JgMDX3N8g8aGVOMvbB7MjZNlu6/FAMD/2DfXWKMuUeMwWe5/GNz06bWfVgjI/9q3zHPIHGD+RT9kM+/Y7AsiAcGPm3f4QPiB77N+YDv8M8c40wj8fZi41XG643EH8Yg4yXNJ24/lGDbBri6dFYZIKD39PQb32IMwcWkrQouX2CGh79b5Cxj48af2vHzjO0E33hcbQvFd6yc35hNrV1A7pHYsOFnFkxGLQ02LbX/31kcdUxMsK22/F+wMn/+5Nkl4Axz48Zfmw3ftDQseC6Sqmgv2FY3+vs/VbJ9dPTH9j1lQV8E0oViIujvH0nK8YW9k/rG9r+LeHyxefNvi1Ja4EyaMgcHv2Jp8T1lEozHXsDpxwD29fbeat+7P3t73908jh9S26mfuvr6PlikHb+eqbK3971Pjrl0LADGA+0fGbmv8H0qmsOmvF3pPKMMz+v5R0but7b+rjjq7aaOGNutdk+2zeSlDMblbGvjQiv/nqK2zrFp02+sL95lZbAwM5ewLfojV2+3Sfurgu3v7bu3GweMNxjxWTcE2732HSdH1xlpL/MHH26Zcbdt0MdvioGBj9l3+AHfItrwQbW/+Rzja5YRn7FmINbwHSJ/OseJ2H12XbD5YBM7Z2/ve4ppWQb3n7lgO8fI2SsTkMlIgE4XJv6/0oL4B4qcdfT1MckvNTLpOdOq7hjkuKopGqoLZg4bN/7C2sEOW/nBCRds2A8RUgQS2hCBw+vq77+jFKjbgV3E/n7O5mcX37TgdSDYYtGgzdSzsikEU2za9LB9jy0ISNItLY5MHCMjP7D8CER2PnwBre801uvzPqj7HKHSic8D7LwMDNxheakf37JYhrgoj5ORkQeKXA7Px47PXU0hNB58AZ1tZAzF4lmtZ/JkLiCcOrElgG/7+t5r+WMXJnxbHd+ramOMPuntXdkcV+3gY4l+o83h28m01+epi0sWT/x4rdnOCVu5X8YDJ3P9/X9n+avjqTv9MDa9HSkGBj5k311kZPcZgUD78FMu/9hML+uNjHzPviNuMKeJf9EH2DAdbd0azPn3H+07/HC1kT4PQVzNx3fMS/xEPCBtOi+6N1fFrUEJtq3OoaFvF9OyjMHBD9vxvzZeYGR3ClGQnmGmZBIuMeH0qyJ3GcPDX7bj7NJdY2ShaCcYWkx3YzoBryUYHv5W8cnhgg0R1V6wIdbSHZ3xwGI1NFR/TYLX006wVQXUb+x7fPEOI0Ftodk/9ruy2mFw8FOWn91LFhS/XDV+fSxoLNxp8FxV2gGaKIaGvmpl4N+qsIg6coLtI1bnT4pPnWF0lBMJFmXaGjuGaT2TI2It3eGaCBB4/f2IBsZ2nNRUBUxdsPX2zrU6/0/xKQ+feyyUMaamIhjIg134jEUUH+LLq82Wm6x/vtMc353ARdv7LW9cnmdMUXZdqPp3HGNM8DfS5doQbYs81fR+LEVLsMVJIW0LUUGdtJe/UX9aVsryfVjsQPrOHZf2mD+pQM2VVbW5yrBhLDuiDNJgdzCXr+q7KtPy0vpz5UWZfC5fQSjvYBJn8EGsBWl+iG8YC8wDxkV6EhdtHMvOsGsybU/LSRm28f8oK2WkaVeu6JRg2+pMA1SAhwV6es4wnmkkELK1zbY2k4fBnStruS3a+beqb978iB3nsiiiiYVn7DPg6o5UAFE2OvrD5sLCrgCfx8KmTb+w8rikmxdsXPrKiTUWow0bftSsZ3T0XrO/7qMqvB7YiWD7lX3P4tIKgH19w5bus8Y7jPV32w0M/K3xfcb3G//O+CFjeu/OtUa/TFW/NJzWx4IWiw4Bysnlzxw2b36s6YORkY1Nbtz4UNtFfWjoS1YW7YnLZfQxPqBf64ItV87GjT+zdPc062rn94EB7q1stbcVcOtjqROOJdY2bfr1k21nPODLHFzADFt5CCAWKhY07IpFoC7Y8G2KaDtjPMZ2q3/xa5Qb/VZvy/iMvNjGGGA+4EfKv8p8cWOzne36OAVp+vq4VBKirSxU05MhRK1f1mbxTtOV25GeNIyO/sS+Iy2MseRMkQo2Thw2bXqkOOIgxvktDcQd6o845vVP5ISNEysfc/SD29Xf/8niaNjsbRwa+lbpRAw7+vrYmUxt4OrEP9rJ5r3N8ZHu7vL/sL239+ZavqrvUjKmo8wUcYuBX86Pvii3oRNs2PCQ5Sv7c+PG1gu72/u7bCdjZHT0p812psBvbAB429db2patubZTTiAdN319f9/8nN7aEbfTcFVovHLFlBJsW5UEihw2bNhkxxFrZxtZ6GOxKAe6MpfbxLqlKKGO/n4mHWeq3JCa7hRU7VplE6p+SW54+F/sGDtYiCLs8p2z4eGvWmDLLy4u2N7cTJcTbLkdJYRaby9n09RDXhd8iCReBtwOrbRclhlPsLHzd77xbUbqYqeD9CwE2HhNkbKFnp7TjVyipl9oOwKY/PiUOmP3bEFGsKX1xb2IrYWfwF4FYqKvjzTcm0e73N9xTyB+r8IXcPowRBt9TCCknpUmBO4vUtaxceNm8zv5sJO2eT1DQ6NFihZI621GtOE7Ai7jsjqWOuGq0kIT8HGAr2hzuf18v2FDvS0ITN/tDNEW88XrqS6eAfw2MICYYTeb9nvbvX76jN2NOGliEZzqwuL94bbhO8rEXsYePo0dt42Fhe3hJwPMrbjdgT6PcV8+8fJL4LSBuqiT+knbsi31EcLL00PmbWthTYFg6+9/V00AV8GlZy5B+5hhrnl5E4X3L3ON9rKj3ZpvbvNsGx/59975ZX38PNdsWW/pflYcGRvceuC3Y+ALYkWcEJT9R99ydaITETo6+oClp7x51obPFt92Br/NIr0VY4l9l+5O8sCGt9P7mrng8QY7EZQbM/MuB4Tr4OAXLB872NF2yqPtXl4aY2PcjIzkf7knhT9IE+Wm8crLFVN2XbCFo8XxyYMC9YUaDAxwTw7CgAUqdowITkwSBjSBokqOcVn0l0UpZYyOcj8ICzFPDTFB0p2Rll2Dg18rcrQwNPR5O0ZeFk4Ws1SoXGaB7H3ZYO2CLQQO7YiHAVZYwHh3kaoFFmlfMKMeFtBWPSxi7DDl0BK4pCWg4y/3TV6wRflc7kqDMAHuhiJlC77jySVq2hL36+BLFnJEMMGxvoCAfH2+8OOHanBnV8l9TP9XhSF+ZIG+zPqlvhPqPiQNCz9tiYVlRVvB5pfM8XlaFztL1Hep5avfHO+X2LEDX8diXh5LnbDaNwCh4r6i/YwH6kI0Rfvhpc22VuFjlcuYYVcImBXm1/yOYX8/L6VM209dsSOKAETUxxzEn5Q38bbm6bb5/KVs6mB++o5bfz+7j2PvMPsOF20OG4kRy2u+5RK4n1hQdgjtdIEsX5L0S/mMb8j4dmGAvSmGhzc0RW8n4BJ0by9jn/Lon8U2p39tdT3SZLrDxQkaMcT5S+OvkvGNTbR3rrWrdVKBkNmw4cfFpzpGRr5redjJXNLc6amCNjvrP9pPG3lYJOptCYzWWJjorSTDw+yEXW8nWu+1OvHBw02m4ApJ1Q/Dw3dbvrgVwwVPWbBxby3jlnlAX7cE+mRvPxgaIk5Eefgh1iLmcSqa6YPOb7UYGPiolUG51ROJGJeiU4JtK3JldicLbNr0c2NMToIZAYSJ7EFtLHImmAPBzxelVNC0JlyQ4JnCz+ARQkEWNAImwYCzegLGtRYEuB+oLNpoRzvBNjz8gyKVw4NhurPGgs2iicChjuA1FgweLHK14IIK+8gT7aNt7QRbiCFEFwIKu2LRnF+kbMFtoi20n0CJIOIsn7wEmljMlpWCF8jX54JtbD/QHvxAn4UfaBsLBr6fWVucyO8iJ+57RIj6Ap4TbEND/2zH2Dnk9THYiBglLwti9O2iInUL7Hi2nl4mgE9OyOTHG20PhjCkHtoc7ce2GTauy5fl/alo8uCv9MQkL9i8/W8yxutzEGv0EcKGuvBhulMRwrSbCwplYSP9xBjCZnxKvfm5lcLbjMhm3DAmYxxWBVt68zplh+Bo2VEWbJw4MG8h/g7B2n5XDLHNCRxjtrd3lvn3C80xmcLvTcPW2CHCry5UiXWBkRHEDHMOMjbp17hEnRdsqeDDZ97my0wQMdf+xf7Szivs+48VqfwS3dDQBrMXGxj7zDc/QazGGred+R+XofGHC4yqv7GFByf6+jjOuLrY0vxvK7N1ouECMuY24xWfvLM46hgYuM2+wwfEIOY2ZdEnjNPIVxVsnKATC/FTiGOfB1WxhogeHPxnay91U/bbm3bmTo4HBri3mhNUxhnj1OdDNeYF6PuhoS82fYlP+/vfWyvX53y0hfFQHZeiU4Jtq3Gi9yx0A4ODnGET2FmMEA1MNiZxy6404IGhoTvtewIFARPxQLBkYhEECHAELSbZjTZpW0EQIDp9IawLtupC7WfOCBTSImwImgQG8lBHkIlfDmjAAxr5U0HqAaozwRZnjL5TWUVLSIb/IgiSj6AduxXsbHQu2KoiouWH8Dd+QxyGH2gXIoz/z7FxVH9p8sAA94awsOG/6Gd/dUUKX+jxG2I3xAqLB/7Dz9RB385pBvUULthYPGhPBG9fuNLxNDbLl9ZAa7xhDwt0XOKkDtoe7ceu2bYIlx90Ae47/BbjwPul6mtvf+yckifajxBgEYy66Oe0j7sp1qoM8ZbuuN1ki/7NNeGTwv0Vt09g75LaOPTLvgjy8A1jkHqi3qpgYyGlDyACK8RVXbBhW3//WjsW45YTG8/L5dLUdv7f24uPw9et/qwLNuJHTrAxB+uCLcCuZG8vYxO/ME6xifwudvr61jdPbv0SKT4jLceY3/iI/+PPS5p+CPhl9zhpo/50fJVFtQtXysIG5n7YcFHTJ5Tlt5rQpvAF/XJdUYLDBRt+IC7kBBtzfF6p71xYRryOy+Xc51x+yI2dMK+fNoWv+D92X2zpq7GTMUH6WEN83g8MfK5I0QI7g319HKftUa63P/Up6OtjHKY74y4E6/NjZ2bXBZtPenF8ciPmdMPvjWPixOWT8o5BTkT6fTwsaky6EAEs5BHsg9xs/+kil8MFG4svYocAE8F5eU0YDg5+3L6nHgIzwYIFgoDA5E3rod52O2AENIJsnP2OJaBCGBJ4yzsx5KnC01fLxx7qiHzOzuur1+OLKgtU+JvAyGJG+vABdfKXvptb21X1hY5gHf3sYqMq2FoLIiSQpgsoeaIO7o8p30g+MvIt+55+ze3Y1sd7nXUhDdxPtB/7GTP4OrUn2o9diy3Q/22RswUeDGmNIYQeZ+xLrQ1lwebpqAumi3AItLS+tJ9z7ekmqSP6GDto/yzz+fcLy+vo719naejDEFb1h198bJEmhB1jKua/t60u2OgHyNhg3Pp8TOFijfoZRyz6+J5xgaAg3zVme/k9kYODn7Dv04Wf+YToaF0OHBn5tn0X8w67Y+eXMcEJE3m4Z7Qs2LDHX2VETGAeIcLCHvJzAkQ/0x7KYfzyPeUzBrA50s2s+b0ljklDGUus/R8vjjp8h4sxBfEfbaX8KJu/1BWM2yoYr+XXFg0M8DANfqBeyqGPow34jrYuLPWd31ZA25lD9DVjYllzNzFA3OjtxX7sCzFFu1IfXG3llk+u+/t5fyPlYgP1c3JQ7gMXzIhFYgR2MCbIQ9nXNHf0Uvh4oJ+okzKJ89M137YXSrBtJa6oCZbpAE+f9vYyETlDI0Aw0VnMfFJUF1AuN7mAqi5oBPrIF4sZ7x8r3zjrgo1gS7AJweYLexV9fUxQ6kFQVhfqqMPr4bsqvJ5uCbbcLx3EwtFOsLX6trP6Fljg+0SRogXvHxa+nL+jrtTvBOqqmEKIUReLFLZ6/rxgi/6JtAR26qJtUc+yTB0Itpw/Ul+Mxfplcd+9wJbYyQzBxRig36PtLbvwYxUuxFiEUsFavikbeDrawKJCO2K3Im1/lbm2bElSp/dzTpwGfBeGBZ02s/DPt+/Kux6+K8q4YtHvVLAxHyFix8ctvkkxOMgTj/gx5i++pO/wPbbMNtv/pkjtGB3lHivSMsZDfC0ujTOelvU0tCuER9hAvKCf6i/s9l93YQxhD+OAvLErTn7qIg4RX+hvvwzpafhLuhBC7OCVT0R9vISApI2LzNbyT475ZVDGMvUzlpnXpGU8M8f4y2fqIxbzf77HroVFKY7WbnZ6EkIb8EHMjepDBwg2/Ma8RlgN1kTl8PDX7XvaQXsYF/Qbggl/hJ9usv4trwvDw7ywu9z+auz3eM7ONeMC27Ej2knZ5fuEXZwTsyiT+vE9435rzLltlRJsW4ErbALUb+yfLgwNfcZsIIgQQAhKIVTq2+UuNJjMBL8QeeQhQDCZyu3KCxXyE7hago1HvavwNARYAkEEpVg4y/VQdxWevyogsHFLCrZcQOlcsFXTgby/8UHV38Gltvg9WOR2uFBGaLNQhDBfbEExJ9jiEhbjgQWjembr/88LNuyMxR9/TEywVe1pjRcYArKdn70Mxkj11yBagjX6ygVrXbDFzgULSgiSdBxU69saDFuYC+WFPIULNtrSmmfTJdi8XOqGlB2LPuKD9NQzWDpJ9b5m7MXJGWOPXdBUsCE6sJf6QxwwHlyo+Xir3zPaijmQMcAccBHrtiBygtiHnSGimG/UEbbjx6pgo1ziFLazO1fe3eLeOT9OOuYgcz7GcohN/rog9DpdqPmx8i0ZrSeYKQtRSZ7ou4gN5R3knGAbHi7vFPb3v9u+p9zYuYt+S/2EnXOLHA6e0PZ85KFsTg4+Uxx1+PzjxJO+ow+wm/ETts8tjQcX5yHMJ7NjvzOw64ItgovYnsttwOffuTU4yA2yf2V8o5EbwTlD4TIhQmZi5Ifjc+B7DyStwB6BL7+AIlJCQMQWeASKcrvaC7ZYgJmInLHW73fwNExwghKBg8md2+lgEo8l2KoCot1DAKQnQLAQEKgJTF72xMqPoNKyr7P66jsgoOXvCIa+kNXrCXKps3x274KN+ljs8KUHyfaCjXSIZNKxYKR1uT/ygo3+qo6LdnZWWX8Iov2ObM7Pwdzl2m/Y9/g6bPNFMi/YcoK10zZMJ/FB+1/k4B2BrXHjAmigcpnKhRVtTf3CHKP8ej/7uGXhjRMNH7dVO7xc/M3iHDtmnq7Vd/g/LRsxSF9jS8z3nOgIwYZgrM5Ttzsv2LCHtkY+7Albgu5TfMB70YaHv9c8+cEGpz/IVf0lDC8/FSwLmukCLaHLOEasxPyIeFav38n/3WcpXLDhh1y/BXO+Y2yHYOU1G+U40epbGDtbzLe03/jLSVHLB61xEfNmjtlYFbW0n/6N3UXGhItRLze3m5r6a7y4tzNSgm3a2dtbvjQQ8JflItZ43xcLYSyknKkx6CfG6s2iKfr6WJhJx0QOYVS/x8knJpMOMpHiLDEmc9q2bgi2ToQKn3d0wRb+dn/l6wkus0Wm/KSo/6wZ9aVCZEGtf12wYROXWjgDZlHjrDot3/2RBldQFmyxEziRADuWYGPsc/9LLPxuQ76cpbUdNn/ykzJijFNGO8FG+5ljiAYWq2r7txXS/m1ZsLFAx+44Y4FdlOg3WF6gW4KNPmrtqHdHsDH2ycO4jhOWEOKtfHBw8Ku18TMe3M+UH34s31PrbcNnjMHYMcKGdH6ELR6jWnPc/5+iO4Jtdu1BLz9OOyjbhVe538LO8i0R9XExy2ws/yyhjzP6gfGYrjPRzvKJVl2wTTSe7AyUYJt28vbtHPyBAHbWWASZCAx0JhEBhwE/UV5jIjD/VNnwMG/EZ0IRBDmr8jOfauAjf1lAdEew5RYef7EvgTCCkgRbp4KtKkRciFHf9ijYGCssJPgJwVZdoKusjyW/PDhRwUb7t23BVh1XKXxHfmsJtlRQhL/HFhQtwcbYiziEqOuWYCNfzNWcwFnR9krHeCg/Ve3tTdHyW8z3Tk48ghzfMoKtOv7dT/g2nSe58c+4qPYd7aN8TqxuMBurgg17OZ4K1jSO5ezFnrBXgq1OCbZpZ/UsJzA4yM/9xI+9MzE56ySIEaQYvBPlLAtIPy1KL2PzZt6SHZOZgOYTNbcg+KPxnQiIqQm2wUFenpheYtvxBVtv761FihZcRExMsFVfAOr3KVIfizPjaNsUbOxuVDFRwdbXV3+tSV8ftlBGp4JtrPZPhWG3j0P3T/Rlvj3tuaytwPD5zM484ybdyd4ago1ySTMRwUbZ3RRs9D35Ir7VBc7g4IYitYP7qYaHv2FlEYeZ45D2+DvJUtQF27zMJUOOx3zv5MQjyPEtI9iqO/E+1zoTbOkupPcd+Sh/LMFG+9N70tI4Np69E40nOwO7LthiQIo55m62B345lJd3EnQJqAQw7t9hYsZ1/4lyoQWlLxU11OHvTGJSxSUMDwJV1IVUTKR04YHLaguwBy6CMoGBiehn/tRTFQCjo9+377n/jgDOriLBmeARk7ZVT07oeB2xw0CQDsHHU2Tlnaz8Tg7BKhbWcsAE7cuv+6Gz+ghg9bet+y9SpDuN7fzt7O8vv/sOuGBBsMWlvhBs5XtYWoItvSSYXjqC7o+8YKO/CPaIneolj/G4LCu2fLzhq7LAb1cu9x2l8BdEp+9VCwGRE2w8JTpe+yfLZU0RQJ3+u5GUC2NMd+onZ85XgeHhuywNsSP85jfn1wUb7+djoQ2hEQs0ddT7OS88fNymKAvBarnBJU1/BPznzRjn+J6ysbn8xHNZsPmlt/I8dbur883HflWwle0p/7Zl+noL6qK9/KWMC638nGBjfMXYn1uy25925njqt6rd7cjxqiDuzL91AYQfiFfYyE+dVZ9kpRzEeLSDvq2WC8vx0C9fko82uiDjZ89SuL1xPK7MpON+PHsnGk92BkqwTSOXWWAtv8YgsGEDv/sW967F5AnBEoN2oiTvwlKQTOHCgIDCGRJnt0yoxaUzReD3Q+UWZiZfq308Ml6tq3VPEgtJKtjqTzb6QksgJEhyNk2Qow3lergHMHfPidez/Qk2fsQ5hb9UlDRj+ztY3bH1xSIEC2UQ4KmLhw62LcFGm6qC1X3ViZ99LNQFL8Kf9tOudMGeXsFWHQP8rmJvL8fwk/dHq1/dx7ly+J4TlHb3WfmrejjJoS/SnbB5NTHvr99AiKTjIhZot2Eygm1w8GP2HQt0jAViSdmPVVt80aefsT0uidJHOcEW7coJn8kJthT+zjRsp53RDoQvdl1t5Y8UKR0ep1OhM9fGXfln0lq/g+s7UO63dv2cfsf/2wm2XL8Fxxdsg4NfKY46/PUntCPGf73fsKe6G+nvzCRfjAtemp67h02CrbuUYJtGLmsbdP3pUBYZBmxnOwvjk7xLaoEk8PDDv7Xj6cLIBFlsorL8gkvg9wQxAQma2BYB0INLTqwBX3wJboipEGzerv7+jxapWvCn+wgE+ACbCEwEEK9nrIXL69lygs0XuxDUBE33l9fRygc7F2zYVn6BJHCRjL9JG/7GD2ldS7P3Q/Jj7S58WZjxIz73/NuiYONHqqvwS7rYxP13LOTxioFou+fN/XC37xpgV/jPd27IvzUFG0CM8xLWvr53WZrY1a6OobQcH0tVUZpiZIR3afGwEnMs2sHYp+yysPLXMYRgo8/S9i6rjadOBRvt8peppvXj81Z7qn3l6UOw0c+UXX4wgZ8w8n4kJuTmactHKcYXbOX5PTj4SfsOvzBHaQN1McepD6FzV5HS4elIHzte82ppWi/9HS+eR1tSlgXb8PBX7Tv8MDXB1tt7c3HU4SfJ9C2+Sh8WwYaWfWm5fkJJH9Mn+MBPECTYpoNdF2wx4MQqc5eugF8O/UtjeoYcgYkBngbziZB8PK5+e1FTHYOD/C5c7GixMC6wyThUE1/Y6Gd5MZkIyNjHu73KIiCFCxXEQ1VIMRHrL3wFHpxisfadAurh7LDdbiHwehBUcRmM4EM99bdwu10scHEGTNupJ/zNk4flnUZfvOgjbPP7C/v6uMTEguf1hM87r488/AZg+ceeAT+b1NfHJCU4Erzc37C395as31uXoPEFAZOxFIKlnWDDpgjYBNUI2Ok44n6TdoItdwk7zd+O7qve3jXZfmXB898fZIEKAUL5S8wvH8zeC+o2MdYYB9hFm5hL9FE7wTZe+yfH6hioYuPGn9tY/7al+6S1k5+doW76mPfzfbZ54pSbHyn83rW4lYLYweIYJzq0o/w6BhdWt9j3jI24J8zn18jIpiJVCz6eWETTcYud9RdXt8qOBZr5h995qWrZF/5CboQCY5X52ho/aZs9HaKA+uPkI8r1sQCr5bvNtJGY07ok3uqfsiDasOEB+w57EGKIIsYCIouXzd5eG58+xvB3CF98Un7PnPuDX38gDe1jHPo89DH8d83xyJWG6Pe0XSlcaFNfKqzIk8ad3O5kCKDw7yIra3ORwuFl499qv7kd1fve/CevKBd7IhbmXusRgi1OviPuR3zI3a9YtXci8WRnoATbtLE68AP+dCiCjeAVi1+coU5lsJIXzrfAl/9BeK87nVQEgfk2eeq7HoDLbfzEDLsEPNBQDWT83mT6I9X+4+/tBBuBvPyyxQBnfqOjP2zWMzp6v30u7zBQ78aN5TN236HsnmCrXrIF2IWQIGjFbx5yZu1tikWyvkCNXR9vsL+t5ssAPwuDH0ZGfmD8obX7l9m0LBB9fZRJPSw8+DvdCayL660v2OCC2u5EgDbRz97+e40/rNkR8EvB9H/sZMYCFONtegVbb+/6opYtA8Raby8LZvxwf12g0u7h4XuKHA586pcw3T/4vuqXQH7c5gVbgIW3rw+hcoPZN2SfN9XGq9dPmSzQsQvm87UqHBFT/usfl1h/fczaw8KOuKGffFxX59vYgi0/nv1EMezhB/dX1mwJ5AXbXEtfjpv4mku/fX2r7Tht5L7Cz1ibWrELO3zupDGkLFyB23e+2TVo/vuC8Yv2mTZFX3cm2HKxBmHuu4yMH798Ozj4Zfu+PC4Q0L29tIP2I6QjxuReLizB1n1KsE0b213WGBh4rx3nLDkd3NUzwsmSwb7QxEf+sqjf/8KZdioUPWi0e8K0HRAWvb3XNyd/wAUbQion2DzIDA1N7FcfCBr9/e9pBsIUrXsAuyPY+vqGa4EtB8SEt4uFkrbxuo52P9GVqw8/LLQ2/UMzwE8GCEl/LQq+jss1XNaJBdb9sG0JNkhaxvk8Gwf1J0Y7BWPOx3HcVpDu0DKXqKd8CQZsScGGL4aGvl7U1F24WGM+ETcYVyyOcfmXMUg/+OLY27vWxkf+hK0KTrg2bGidqPi4Ze6m47Yu2BgLnWLDhh9ZfvqIHS3sZhe4NR/YtR4P3s4QOfX55uW3E2yQWxHqJ4vMP56ArP52ZjUO+Eko9qeCjTp4gW59t3wsjI5y+wPzh5ML2oQfGDt3FynyoB6POcQ58vA7rOMJNsbF/HHLzgHf8IP1Hlsol7bHDj67wtVfOpBg6z4l2KaFuftZgN9Hlj4dyqITl7AY3PnyJkZ+IPv9RY11+KLF2aLfi9BatHgMvPwaiBz8LJLJxsJ9gU3CVLAR8GPXI+5hi4kLmZCDFkA2dCRWCPa9vZTxNquzKtioh8UrgvR4gi0WjRA2qWDDb4jJ8QPbwAD3H7KYEbh9QcsLtnb1hR/mWNsWlxbMTsBvMvoOBOXjZ8QHuyf4AF/Tl15PXrBhEwKHIDlRwYbPY9Fqf0/f2KT91HmTLQhcJsq/9iYHxszw8AbLS7tpP2QcMpYZJ/iYhdrbXxds1Rfndlew+UL2iQm1aTz4PWvsyLOzhmBmAY3+Dvu9z5ycDNw+rmhjJ7O398bSvGrN37EFG/OO+w45ARwLo6P3WlrKih0qTq4YO+k4XWTp2s8B+tzjJDs7xMrZ5uOqWGAcjC3YqK+T+e0niOXfcPV4TR0x9hlnfkmTnbkNG/K/MlMFcx2fux9oE8KGuIWtc01Al2/LSEF/+UkGeYjbc0pztL0Aws+I3E8029YJGL99ffiM8ug/+i7GnM97Cbbp4NQEG4nJRGYKMcGGc8UqueemOvnYFRka+pQd52wNoRHBi4HKhI3BOlX6wjE6+oAFu/KZIoLRL6MxAdMdGern+1l2fJ3l/aHZX17sCOb8CHDrPW2+aHIJI+D3R8RiysRlESUgYZOLKQ+miJWFVt7dVm5L8IHNmx+x+r9ndpCuVc/QUEsE+82zfA8jSLcuBfJahbTtbhc2sVinC1HYhN/wwXyr912W/sel9rMw0f7W+87SRRPh8ZEJ1hd+wOZ3WJ1cjvlOs46qkKWt3N/mvqfPWFBh2IGfWcwYRwTnGEdLzN5vFqU43P5UsKQLZ9DtSx9GwabyQxjpuA3/dUrSY6OPNxYhXqOAEKX9VTAe8KfbHm2HLA6IVfzLAoEvy+1PL0XRBn+1zXjtnyypl7Lwy0xr0z9Z/a25MREw3rh9oa8P/yAWiBmMdRZFxh39zbG4DyrtA2yYZ2MFwf7dyjj+z6ZNAwP/YGkQuhfZ/1uvHvKHX/Ar9SCCqcMFW4xvFnP34Vubc5S+YYwGEAWcaA0MfKhIR6wJsUbs4F4x+j78jv1cJv98U5Sk8Et3n7Dj5GXse7v7+z9cpPD6vB7aE2KB8ik3fNLyCz9KPzr6rzW/8MDD0NAXLA11XfzkcY75eGOuEWuwAZ/EPZaMIV5z8ZFmu+tx81fNeNrXxwLMuGP+UAcnXfgiBJvHxeHhb1kZrdtM3LbN1mZ+B5T2IdrId5N9/6siFXP78/YdfuBEGRsjHlJ2jMtrLd0Xm+WlfQaw2/uNscG8or0xVyiT+dIaD8S8gPcB6ehn5mOcqFN/jM3FHdo70XiyI3Pygm0PowRbR2TAQQY2CzWBjwDIAkvg5S+fCUCcMfoE6N5ApRwmKYGA4EWAZ2IgfiLwMxmr9ROA+D/fERQIDkxcJiFBHFIOn7GfAEkAo3zKYuL5IuAkOOeESgQnjrHwk5/Jjk3VeviOYwQ47CEYpPVwDP/6DcPejqAHUreNdpCWYEnbCA7YkPqcPAQ2jiHEqCvaT5+FXXxHObH44Gfy8beT+qp+IAgSsMhHevJSTzviE9Lge/L4IlYfR/zlM3YRQGkP/UYd6cIWC2dK8mIbdhOo8T/tIX8EZMpN65sIyUO9Md6og3LpU+rItRvG2MMWxkHsUmAnbelW+yfDqI8y6Q/Gts8hxC67mwhSTpqq4DtuJ2A3rfX7wrETH+IUu+lvxiZton9y/ue76jgOn/rJjzP1JWXzN8YWnxm3LPLhV+YTfcV8Iw0kP39jbFAm9UQdMHyezhfGPmWGvXwOe4kH2BH20nbKZbyHyMEmbKNfY77FfOA7fEOZOb+4oHa/kC/md4wvSP3BaBNjE9vScYPviZv4hnrxDXOFPNgdPojYAfEVtuLfiI9hG3bTPnxFOaQnP36gTOzFbvwUc570+IX5kB6P+RmM+Rxtpz2UX7UzGPXRZuYntqbt5i+fY42JGIEPcutatJFyxrK3Op53ZqKxpibYDjGGYHttvhLRB11MkAiaITT4S2BhoEfgJX23BirlMPAjqDFBmVAECernb0wS7EvrJ8gx0QgGHGfyhd1MRiYYwTeCIxOZdExQ6iHQkCcWlmr5Vfs4jh/Ih42UTV3Uw1+CALYS3Cif4JTWwzE+Yy/lUW6Qz7FwUjZpw+8EWAJt2JTahb30C+mog0UXW8IHtJ3yKDeCZuq3ydZH2/AneagDX+CHIPXzXYwf6sHv5KVsbMiVj10EScqmLeSNxSLyRZ40L8GVvLEQ0R7yR/DmGOWndU6EYV+MA+rBLuqh32McVNuPb+l/xlf4H1urtkyl/ZMh9cFYyLANG7GVerE9FSKcQHGpsMrYVSZdiB3ajM2MkZhT1f5O7Qi/+q5Ka34xroJ8xhcsnviGv/QzaSH9EeOW8qgz5ivpgqQlL2VRJuOT8vkbY5XysT3iXdpXOXspN+ylDPxHHdiEDdiEbZE++pT/812Mh078wngLWyH1xtzFjmgXaWPOp/ONv3zGrpjDMVdSf0fZUU6IGvKGbdgdsYD2pP6MsRvxLvom5g71Ym8cT+cnpGx8T9vpw5hrOTshx7AVP1XnGf6MdnOM9lAe9VN2jNGom/TkIw/tG8/etN92ZnZHsP2B8Y+Nr7EO+/dWp4gtMvAYzAxCBiODmIHJIGUCpIE3JkGunMmS8ig3ghMTJOrnL/bEJMFO0gfDbvJhJ/aSjwkJowzKZNEjHZOQ8kjP97nyU9uiHuzDDwSvtB6CM38JBJTF8Vw95MGGdGFJy+d7jpOOciDlhN9Tn4Vtqd9y7cemtF7KIhDxd7L1cTzalvZV+CL8wXeUTRrSpvVTVrVsmLOLdlEfPiJvmi8YdsWCQL5qu6OOXP7xGHmr44B6YgGItlfbj/34lfG1pdo/WVJnOh7oJ+rEdhbcEG9xAoQoC/KZ7zlOOhY08uF/2ouf0nGeqx+GDaSlnbQ9/ApTP3IM32Mn/od8X41P0U8xLyIt+WNOUmaM3ZgnfB99RVnt+iqdBzEOohzKrJZDWv4fc4Y86fGcf6r1YHvMt/AL/48xEr6I8mPORTuiTFj1D22nvCDl8h3l4NvUH9Vy0nET/oz82Mxx6iI/5VBetCVspI1RZpSfjsucnRHfqCvKwk/kqfqUsvgubKVd5KHcdJxG+qifY53YK5rGem2htdBcaK/9jGixjgQbiX/feJTxFcbTzPEP5isSfXAyaJlQDHoGMoOTwZpOuC01QGNCUQ/1Uy/1Y0cEDOwjXZovJhZ5mUTkx15IOfwlL8fIT7poa6SHuUlerQeShry5eiDft6sn7IhjUSZM20A6GGVF2nZ2pXlzdvFdtd6p1JfLH/WlbFd3rlyYK5f8ndrFcdJFHvJ3WnenpIxqXam/07ZH+0m3pds/WUZ7qJM6qBP7mXuxQIY4aCdKU7FDPvJj80T8Hm2PdlMGcz8YcSj6lL/h4/BzWh9/q/1DHhjfUWbEubSOTvyd2kueqr3VcsK/fBfjI45TVif1tPNLlBc+ST/n2hFlhj2kTX1R9Qd1j1dO2EaeNH/YEH0TdUZ6/lI+x9OyJ2InTMuq2lkti3Thp+gDjqXpIw92dWrvzky0FZtiTa3VkWCDTzPuZnymcV/j84wvNB5v/NOenoFP5CsTnQzAGNhVxrFcvm5xsvWneSIwVhkBI62D74Lj1QGreaPsCGjj1VM9Xi07LTfypGWl6VNG3jR/ylw5kWey9VXzp8z5I8rNlZeyWm7VrlyeYJo3zd9p3Z2Ssqp2QtodjO/S+juxoVouf7dEG3IMG9P6Y6GMBa7KOBYL31RtTW2oMo7l0sR37cqK/6dM8wfjWFrOWJxIWWna+H96fCymeXNMy6t+hmOVCavlBcfKHxyrjGr++Bzp089pmSnTNNXyU3ZazmTyRL70cy79zsqZd5vGOtX48kJzsVmGBkOLocnQZm0F2zOM+xifazzC+DLjKT09/3Nh2eFinelgrjKXvtvM1RvMpRdFsXtM51uItlSIQsRZ9btUrE11rqY2VDlWmrSMsdKNx1w5YzFXRnC8tNXjY7GatxPmyqkyly9lLk+VuXzBTtJW0+SYy1dlLl/K6cqzsxFt1fNq4x8ZjzSivdBg4wq2XY0Itr2NBxsPN77EeJLxL+xs8Df5CkVRFEVRFMXOOf9xk1pnmL462fhS4wuMzzEi2NBi4wq23Y3PNh5oPMx4nPGVxv/W0/Omm/OViqIoiqIoip3z/H9ybdVzYqG10FwHGdFgaDE0GdosdFoT/AcFt4uRm9z2NMaTovzaQfHgQc9f9fTc+NN8xaIoiqIoiuL4REsd+FbTVfHAAVqLV3rwS1N7GdFiaLInd9cCIdh4GoEtON7/wU1vXEvlmipbdVwW/fOenhde3tMz74n8tWlRFEVRFEWxPdFQp8w3TfUXxrgcygMHaC6eEEWDocXGFWxswXGzG1tybM0933iMkZe6oQT/0sqelTdCFEVRFEVRzBOx9mdrTEv9lZH3r/2J8VgjWgvNxTMEaDC0GJoMfVYSbIAvuFaKouPaKZdF431s6S7bG4yn9/S8ZLCn5/qH8gaJoiiKoiiKLaKZ0E49f238cyO7a7yJg921eP8a2gsNhhaL+9dqSHfZ2IpD4cXTooca4142Hj9lG48nG87r6XnT7f5IuiiKoiiKoljm3CdcK+0zUGin/278UyO/bsAVTB42QGuhudIX5o4r2NKnRbmOiuLjuiqPm/IUA5dGqQjRdrrxHOPbe3pOfU9Pz8Xf6OmZ9WjeYFEURVEUxR2dc/+jp+e6n/f0XP49k0ofNB12temkc43srCHWeFEuWuoPjbzvlh8q4EHP2F2Lp0Nr96+lqO6y8R4Q7mWLJ0a5NEoFIdq4PPpG41nG84wXGy8zXmHEwGuM7yg4UxRFcSfitRNgLr8oitsHQ+egedA+aCC0EJoIbfRmI1qJy6CINe5be7ExLoXyZGjcu5Y+bNCRYIt72eK3RSmI97Kloo3Lo9zTxk1z7LZhzJnGs40oyfONbzNeaLzIiOGiKIqiKIo7EtE4EM1zgREN9BYjmghtxK7a64zcs8ZlUDQUYo3XeMSDBlzRjFd5jLu7BjiY7rLFpdFUtPEQApdHue7KzXIoRYzgCVJ23P6H8S+NbzL2G9kChFy3xXhRFEVRFMUdgWgbiM7hNjG0DxoILYQmYlPrFCM/QMDPT6GduAyKlkJT8asGiLW4FIr2CrE2pmADIdiqoo0CEW1s3XG9lUdQjzJyXxvCDdXYZ8QwtvwQcCjKPzPyJl/4elEURVEUxR2EoW/QOmgetA8aCC30KiO3kCHU2FX7AyM/+ZkTa1wKjQcNxt1dSxHKLrfTxj1tPIjAEw1UinBja4+nSDGI138cb+SSKSIOY9mFgyhMURRFURTFHYGhb9A6aB60DxoILYQmQhuhkRBq3FaGduK5ALQUmirdWZuwWAuEaKOAEG1cX+WmOJ5kQBlSKZWz48arPzCIrT523o42Yijbf5AXw4miKIqiKO5IDJ2D5kH7oIG435/bx9BGbG6hlbhCiXbip6fQUl0Ra4HYZYudNm6Gi6dHUYZUymVSdtwwBIN4BQgCDiXJDXUYG+RdI6IoiqIoijsCU42D5kH7INDQQmgiLn2ikUKooZ3QUGipEGuhs2KjbNKIAigs3W2jMtRhiDd23djiQ8BhGL9FipGQnbiUiDtRFEVRFMXtkVVdE3oH7YMGQguhidBG3KcWO2rx2o7qrtqUxVogJ9qoMIQbl0oxBIMgAg4DMTSIshRFURRFUdyRmGodtA9EB6GH2NQKoRY7altMrKVIhVuIt1TApSIuhFyVGC6KoiiKorg9s6pvQvuEOIOhjVKRlgq1LYqoJBiVVwVclWG0KIqiKIrijsKc5gk9lBNpwWlFtfJgKuJSpg0QRVEURVHcnpnTOsGcPtpukDNeFEVRFEVxe6cgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCNsBenr+P/GJbf3IDe/dAAAAAElFTk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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
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    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};
d={1:5:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b*d,3)+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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  </question>

<!-- question: 361118  -->
  <question type="formulas">
    <name>
      <text>L62- a D b P c2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Simplify by adding, subtracting, multiplying or dividing, as indicated:
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                              e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                              since it is always transformed into px units
                          sizeN              size of the font w/o px, e.g. '14'
                          family            family of the font, eg. "Times New Roman", Times, serif
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    function newWidth() {
        var txt = $(".formulas_number").val();
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p>Simplify:&nbsp;&nbsp;</p>
            </td>
            <td width="25%">
                <p><span class="" style="color: rgb(51, 51, 51);"><span><span class="" style="color: rgb(51, 51, 51);">{a}&nbsp;\( \div \)</span></span></span><span><span class="" style="color: rgb(51, 51, 51);"><span><span class="" style="color: rgb(51, 51, 51);"> </span></span></span><span class="" style="color: rgb(51, 51, 51);"><span><span class="" style="color: rgb(51, 51, 51);">{b}</span></span> + <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup></span></span></p>
            </td>
            <td>
                <p>&nbsp; &nbsp; &nbsp;</p>
            </td>
            <td>
                <h3 style="text-align: left;">Exponents:&nbsp;<span class="" style="color: rgb(255, 51, 102);"> {c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup>
                    <p></p>
                </h3>
            </td>
            <td>
                <p><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></p>
            </td>
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        <tr>
            <td>
                <p>&nbsp;</p>
            </td>
            <td>
                <p><span class="" style="color: rgb(51, 51, 51);"><u><span class="" style="color: rgb(51, 102, 255);">{a}&nbsp;\( \div \)</span></u></span><span><span class="" style="color: rgb(51, 51, 51);"><u><span class="" style="color: rgb(51, 102, 255);"> </span></u></span><span class="" style="color: rgb(51, 51, 51);"><u><span class="" style="color: rgb(51, 102, 255);">{b}</span></u> + {=c*c}</span></span></p>
            </td>
            <td>
                <p>&nbsp; &nbsp; &nbsp;</p>
            </td>
            <td>
                <h3 style="text-align: left;">divide&nbsp;<span class="" style="color: rgb(51, 102, 255);">{a} \( \div \) {b}</span>
                    <p></p>
                </h3>
            </td>
            <td>
                <p><img src="@@PLUGINFILE@@/ooo-Multiplication.png?time=1624463020172" alt="mult or division" width="200" height="55" role="presentation" class="img-fluid atto_image_button_middle"></p>
            </td>
        </tr>

        <tr>
            <td></td>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">&nbsp; {=a/b} + {=c*c}</span></p>
            </td>
            <td></td>
            <td>
                <h3>Now add<span class="" style="color: rgb(51, 255, 102);">&nbsp;</span><span class="" style="color: rgb(51, 255, 102);">{=a/b} + {=c*c}</span></h3>
            </td>
            <td>
                <p></p>
                <h3 style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Parentheses" width="201" height="57" role="presentation">
                    <p></p>
                </h3>
            </td>
        </tr>
        <tr>
            <td></td>
            <td style="text-align: center;">
                <p>{ans}</p>
            </td>
            <td>
                <p><br></p>
            </td>
            <td></td>
        </tr>
    </tbody>
</table><br>
<p></p>]]></text>
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gjV+UFbRhB9NTr/0WhePtC2aHjyfykj5wqyHQfrTjH0nfKXr1W9g9wznnOM01NOzg/3+wK3VE7k2zv7cxpip5z1FngXn/+26oVBfN8aN7fQ85nAfpV2RwTUs1Qx6KwERJOKhO2vPQkefPWKHnn9ij5sG0dGX1XtIxtFy2fqYR9dnflfK58oUzrGCfzH6on8Y81NJIAAbPyZcRtVIdyclNycKesVMHDwglRQhmz0+EueKdSN7tHOjmStlOWdK4nq7vXNzt5WCgP6UJbMut59wgnByYMl33jh5sF9UyS/tU7RiQgIKjXCqR/LiFr/yysWjSCgj4ljeplhBLtYJHP03as3KJ+fPWL07onr5UTeRnuT6eXg7Pfli29nHmCQB/G7pynHS8nv37vjOTTBn1KHPZbI7tpKi1owy+G/usub+tCSVs81v3p9HJc28E5393fkSO0A8E6sfZz94gzy7HDGaXXEs6FEUGtEzuxZxL0a/2jDUwdED9nx7EKMSakGqGOFV5hKxmGf0CERC7YjTj6VajY2EDY3r4tSt5rHSVjVNa+vDdGptwfKzNUwmY+UDWzlEUP15WVXevLjt4NdeFubHYsij1tFwxpKkfip7stlmX7p8NkeZd6Km0qegMay2EjSk3luG+Rh+gsH9DK9GnJI/XMIrmnfyNH8mY95x7lpGBfvPtdWbCwHtq0QLLiF0je3ng5dby8nJzSNtYMukals4FKTiPJ0EUc/Ub/S+fyjd/LtxXI2pGs/ZIZP18ywMb5Upy5330mNGgn4cOeshFj6NdI0p7QcQ/GDg8k15mvb3NDdwZRxhvMB8aZrWPK2bFCThTnuc+UBWVWDGwl63vUNztJB7WdPG3HEaoyjk7o55YoC+o/nLBS9kx7y5yjbZ8MldSVU6QkYEwY92oj3pD1xpL9VBMp9Mzb0dmh151/LAjOD8aSqeenMCXRfTQ0OH/YwUU7qToWtINrpXDmc5I7bYSkThxe7txn7tooKz4aLKtGDpH1o4fI5rFDZauOZeXzd8mCh+qWXnuYm5LF77qlylKcmigHFo6RbZ8ONexfMLpc/xY/UlfWqPgl9m1orplcXPs6dnv9E1KdUceisBESTqoSNsjaqDvryGQVtYUqX1jI1ulCj8V+g4pFVWzt1dAsWFiwDz2tC6mKgbdtyAgWxROHQkXkeFGeLOzXysgeymMRznv1hnKvBzuosjDpvlizmzfnL3GyVhdIyA7EsEgX7Ipy9HCGWaAhoBNURMe5O4LTH2spObs3ukeVJXdPvCzW8W/u2UD2q7Rh8bUihQXYf2sXyVdJmNWzpdltxM7kp+2j5XMF7cyooB30C8KAucM4zLh1ztAGhMovbN6kbZhv5gLjGX9P2ZiC2klePlnmdaprzqMVXEiOPTcQUP9cFyZtknl9rjb1YxyoH+3g54na7qYxQ8sJ7/4FY2RF13qyo09DSdFrwCuGR3zC5g3mYe3bj5rx4BcFjAOsfLOHfONrA21C2CFtVkAhutjZ26tjw/UK6fMmae08eVev7Q/a1DG/jGAcaGtqh1iZq9fR0s719NptYATwZMZOt5STjFVTTJ8w/s8wD+4cgCXP3mmulXyVtxkdY825hOhbYcU1T2EjkYA6VniFrXgofuMhJHLBjsfR2cFiA2H7sE2UWZTmdYqT+Efry06Vp5SBjSRVwcJYFemDGkvWk40lx8ias8Ni2y7S7/Fzpj6f/Wlvt9WypG+cbyQMUpGkknR0x0L3GSfYwflSF8uJulBOvi9Glj5SV7bpIntgQCM5/IwujhUI2yEVGAiHs2Oo8qQL61cPOgv1fB0n2gzaMVqgsmLbwO4XxlSk4wgS3qz4+aZPmLvx90Sb79GObWOhLuSY0/y95Xf99s0fbY7ZoPONcWN+IIeYvyBhg8CsHjlYPmlXx2mrdExxpg206R9PYUaSGTt2QCGhOFcQaowH5+SbnaGvicOO0swHVJ6M2MTINBUb1I/yS3ROvu5c13yfsnCMW8IJ3niC+Vyl0pao0oax4Nzg/Jf4dkBtsvX8TO5xlYqQM2/Tta3ZnvOT8NlQ98iybBw9xDy3Uedsb/+GckjlKEOvPVynCX0aSN7WUGFLXjdPPmqLnWP8MhKjYqWSpuNYob+Q4HrbonOCejK0v/5g7J+qgGMuMIdzdB4wBwB12HMLwccvOBA//JsxwqZzizm2/wYIqa6oY1HYCAknVQnbP3RR++LuaLMYb+/t7C5lP6WLuy4+EJaqyFWwQFtZ8y9W+BnHYHEt2hYqZMjqt3qYhTB1dC/3ESe4fbZsxF1mwcXOxiyVibXd64UITnGAEGTt2mgk9KO2dYy0YcHFQr9ShQIL9ebHnN3D3R/1dEuUZdfc0TJdRWhNt7J2MKZTmaE7MBBJ1P2JLuqj76xjBAcLOBZvCAXagPTF69d13evLSd9ty7wDic5ujY57uyugeTp/wC9skLUFr3aTv99WW0be4YwJfYQsQJIg2Rt0POmz33ZLlAUyiR0lHLevf9l4MHf+3bU5vVsaGYSooMxCFZzVOg9bVWx26HUBGTNj0vb841ky/E4jWxh7qbjoeQ8StsydG+X91lHmHGFHEjKFufOeH5xn3Cr15oAKGM4lxBH9wS8J5jrVawvSVrI99NrC8RBcSBdkDf3G9b27X0NzbtFPyBquYX/w72GUzjXOK64dzAPOE9pNUCDA6CvA3OOXHK8Qe69/Qqor6ljhFbaiIfiNh5DIpUAl4EgFOx15aUlmFwIL9dcqD7v6YmepkSlTGFDX2ZL3DASwsezVxfJkfuhCjJ2gmR1jyi3QeE3YhHshEHVkhj6P/m3rVd/0D3UVah+LfTts2O1573YVGx0TFuvpHSBFcbJeBSBRF9o9/SCkDc3XxD4Nyr2YP2PbcjMXSx6OMwtzCkRK++5P0vzRRtQ+bw+ZjDaLOtrYrv3b17+haSN5QEPz/W6d08PrprolyzJWRXQ2JFRlAMdgTLlPN5ZTPmHb+/Uk+YfKzQeta8sXKjgQ12UqLRAbjCFJ28C87h9+nVuiLI6wRMtSnQMce1AlBWJdPL6Pe4STotREM5ZxKio4ft5fHGnd2hO3nxuUjgnf79R6ivdvcks6we4XZGpFl7rmmHT3GvKfH9wGH/vwFeaaw/in4fzoXPvPD67D4l0r3VJOIGB2rjF2XAfZKlyH9fxA3vy7syl6/Gc6pkn3RZv5snOFchmDnLI5Ot/4ZQMf2eHNrrkfy8d3RMlUHRPmDrKHOUjWvqXoebVzYcFj6MNhrS/o+iekOqKORWEjJJz8EIQNcgVRwEJ+aOpwt/WyFGWE3s7D65sgENjpgEQs0EV6ky7SWHCxyObjdqjWW+ITgiKVPwjbGJUpLO6LVAa2qHRgsc16spHkqBRBwPAVPx/ZHSoFkEeI2JwHY3WRrmfaC9olQp/svBnpUuFAG5g7SBckAu3ge4hY5rv3uCXLsuqjwUYmICwQPfQHx/qFbc3IwTJK5QFAcCBFEFfsKqEM2sKcYLfJn3UfDzHSBsmBfEEi0a8TiaG3Qw/vjTftQLzwJoN944ZJ5uThkjN1hBTMcCh0v+ZPHyFHk0OF7eD6eeZ8LXooTnZo3yC6ON/+W9Y4P+/q+cEcQwxxfND5gUz5BawgPcnM+8yOsbK+Rz0zfowZ1ymuB/+YUrRPOD+QdkjxAVeqzLXtXt8AP/vbQlAevyis6urIXqZKHs4P+gcxw5zjZ/QB5xmPoy7/tU9IdUUdK7zCVjgYv4kTErnk60JyZNYIdxkKDYTtH21q60JYR5aqOOzsU18ODmxoyhQE1HW2oK4CsxA3klRdOP27J/6sfLO7jL0rSibogovdNyyau9y+HX5aZUDrQr3FM0PHBSF4v3VtIw8zdKFGOexepWq5nKdUbtyy+Iqfj/gWauwAYXcOZVdrWczHsU3T3GedQCY/Uwka2ba2THaFa+tj9UzfMD4s3GgDOIt7I0nT5/xZqcI2Xud9riuHOCZLpSBI2MbcGWXaxM7XJj12b78G5liMwY4nV7/3Z93HTtk5D8aYckn9G5hjT6aECte5JlXlBucL/dusc5H8eAPJU4kpCjo/KmwYC0Rqlcpn0PnB98cTygsbzuvU+6PNudmvY4FE4dpCWycSfTtsEDad32l6/NpudeXA4878mmtR8V6XWS/9Vv4Z8A5WvNkhN2GFJPytnbkW0Gb6Ew1NuzjX6Cfm3fbb1ktIJKCORWEjJJxgIfm+hc2ChfWQLnDJI66Tb0rKfxwFgltfkCbckpqii60Rop6O0BzSRdLbryBh+1DHA9Fb0MmRh6By+N6McUb5ecF8TMFttEecna9jPnFAG5AT7HhBJiEDe1Q6sHhD0GwbXjBm/wfF4kXxVizXaR24rZY5qGGgsH2ugjPx3mhZ3jnOtAVp8J4jOx5/1quwYR6/eiBGNvaoJ/tU9HJVLk7nQ4XPJDhn3nasGBb55rfs/GDXT8+PK6r+84N59AsYhA2ih3lYofMAac3QeUC5oOOtsDk7bM78QrJsGxaUNwL2Sa8Kr0nkWPZ+yV021owN/0awIwhZO1//Vgj5oaOORWEjJJxgQfmhCBvqxUKOxdN/W81mw/jXzO7VJypFEADIzO6+zi1DlPXWFyRsGM8kXdQXPxRrRA+LOmTKWw6Y8QUIG4TClHd3zo75duFw2xS7VqOVUhFyBQXj87cDsLDjz2F5A2GDgNgdI+xKQcT8x0HYvlCxg0Rix9C7s2Trx/do2x8IG8RytvZzg/YTkoO+hFPYsCs5Z3AbM5b57g4b+liRsNnzs6iS81ORsH3aLkq+VNmDTGNnLg3CpsdWtsNWlbABCDXEcefQayV384LAz4uzgdRlfvW27Ozt7Lih/xBO82+mgvNPSHVEHSu8wlbwjP6PjZAIJk8XzhKf2NhA2CAo49pHyZKHY3URqiepA3A7CwtQcH3nCurN/7z8R3zYHCs8LF90uUIlJUoWdYqV7bqoH1CZyX2qoemXt66KhGDyvXXMeLZp2UwjBFjYQ8sGlUc+aF1LvtSFfv5fYiS+R91yr29yhA2vk4uSuQ/GyOZHIVH1HWHz9c+Cvvt32LbPHmWkdKL21ewYqZQe1LkPErZxKmzm1l7XODMXWYNCx4M5xdz4g1uikN+ZHaON+O7RNg492bCcsOEF+m/9uaa8d3stM3+j78BtS9yGjZLPA8Djn2rfx+ocfOweC5EykqzClqwigzH7hfh0zw/GEiRs2NkMulYPq3CVEzYdU1XzZkH5bJ2Xff3qyyY9n6sHXC0pKyabN7FUlMNbFsgWPdact4HYYS1/fRJSnVHHorAREk6wiPxQhM3Imtbtlxf/B6WmbVluJGCBStMWs2NT/7wIm/91UihvhE3lA21j8Q4SNgjNmQqbP3jTAaRn0vcgbP4Pik3fulzeubWWORZCNvk+vIM1xuwgYox+8Jq4Oe7zs7XueTpXkLUN3Z020lRg0J+zPT8o+10KG+rAOUK/cR5wTpd3jjXSvuGd7nJ4T/kPJkaSZ7wpa7vFSUIvpy+oH9fA+fi3Q8gPDXWs8Apb/tP4B0RI5HJYF6KSmeXfmYkYYVNBwW7W4odiJFEXnpTHVT60TF5AXecK6vQvrMWZSZL09ST3p7KsGzVY5SBa4nvEyb6+9VQ0Gph+eesrmhE6LiMEOh5IEMaz9bG6kqGLMMp6y1n8L77PO5Ag79+OHTZHFtF2wYLyn2+GXSVI25wHomWTHpPUzxVKX/8sBR/e7ZYsy4ynWquw1ZZJKofLH4lV0dFFX+c++JZolExViVrTNVaSVQ4znwgdD+YVc+MP5nBkm1oyswOELU5296kn2YMaqISGfsgsJPTd22rKJ9oftIOxr+oSa9pDucpYr2CesNuE+jGGLO0f+nS25wdjORHwpoOxd+KjTcpfq7kqof7jIWxVzZsX9DdH+4G+41jUv6F7nHytcojrcN3b3cvtuB3Vn7/SawD1m7EPqPw6IKQ6oY5FYSMknGBB+6EIW9G48rdCFw1rYxZiLMjelOSmyzRdbJepzGzThf2gLoaQDW+//EKABRXjmXBPlCzs5Ox+pbnlvP0AqOfbI6EvMse7HbHDBolaovMBCTn0bnnZ2jzhdfm4bW2zu4RFfa/KFhZ7zJu/HeB/p+mJojzTT+wiQihWqxxB+tDX70LYCn0Sih1O3A5FOxjTys64FV3XXA8oUxF7XCDU+7X/OEcQHswF+nUhCRtAXeg7+oS6MTbMA87xCp2Tbe/1cGsvC+R+oSv3uA4wv5C2oPoJqU6oY4VX2PKe0v/BExLB5OoCVOxbOG0gbB/cXlM+b1dbFnWK1sUpTpL71ZNDg+pLDhYeLXumHAYB/QDfFvg+HHfjPBlzRy0ZrSx9rav7aFnSNsyTWR10wVWh2dvXkS/Thltf4fTy48ratUHGt68t8x6Mlo3dYyWlfz3JHIiFvawf+P7Yqk/cEmX5WvvwYeuaMuXeKFn2cIyKYpwjUb53DxaqPECEZtzv9G1X77oqKjpn2jfbhqXglevKiWHWtuXyvjvvqGMthELn3RG20M+kWzPyGflCj5t6X5QRu/16XIaOx9sGxoN58Wetlv3I7SfasP3MeP4a94iybJ810t1ZjJZ4FZQDOm/p2p9svRaqAteLuWa0D5WdHwgb5neiCvVivd62PhpX2oZ3PKjjeELoLiCEDdcK5gxlE1Sk0Ecci2vVf3zKurlVzltF4BrGWDBX6B/OzW6dO1xP/mB+0QauF/z7QRuYi6B6CalOqGNR2AgJJ1jQqhK2z+6qLQt1oYagJOnihIUqG+jCc7pUtGgDLIDHfbtM+PNGWLixCI9TwcKiB4HzZ/Wb3YxMbnZvjXrFKEjYEPwtUezOrXgkRnb2chZ2jMdK6OGXry0nUXi3I8TRK2IoC9k7sj1UBpDts0fKJFc80LeUxx0hsOO3IhH0mWfzB7eRD3XeIUgQS+zOpLrlz7ewYR4ghscPhPYLu2zTe1whM1WQ0c6ePnVNn3C8Oa86FmDPM8553vt3S/aL15r+YJ7MHGN+laDz810KG3ZocV3jHOE6wHgOPu4Iv8X+cmHqUOy4StHxWGnD+d03rJVbuxPMGcZjrwOMB3PrHw8h1RF1rPAK2+En9TdrQiKYHF08/LemzkcOz31L9uqieKBfXV3gIFZYTJ0+FHxwt/zzZOgbC+JHD9YFtZaMblvL7GhhwVsz4Kpyf6cSu1nTVFaWPxIt27HjpQsn6ka9hdOedY8qH8jB+hfaml2RXb2ccpkD6xnJOOXb6UN2qICNalPT9OerjnVMOSzyaCttRCv5NuCjHg6unysL+1wpqzvHyO7e2JWC4Dn9QzvfZCS6R5YFfxUAYugs9LVl6UMqyo/GmjlDWb+wrf7oaflc5wlztErbSerrzK/3HGOecZ79gbD9Q9uZrvO3pkuMmQf0DeWz/97ePaosR1Ry1rzZ1fRph871fm0LfXJk1wFSg+vJiiheD5eq4gQyUK97bND5wTnBLwgT764ti/QXhC09YkPOpwXlg4QN84a5QFn0D9ea6ZO2WbKw/GsN1496xuy2YjyJZve4rp6X9trHMhE9umqsuTaP6ziyX7jG9MeeC/TLCKoei+OPHwj9Q/7mNY+31XR2dB+oI/F6zWAeUNY7HkKqI+pYFDZCwgkWtO9C2EqS4s2ChYVxvyttaDtH++CXkMKUBPnkTmfx/VIXu/kP1pEN3WJN+cyv3nSPKsuBZZOMRK1V6XB2Spy6CyoRNpsjWUmSt2W+FG6dL8fTygsUYkVirAoB+rNE5RFCgAUeizUW8fx5b7lHhwafhl+UmmDaKNA2irctkBOHQsdrg7+SACHEThHGjzGt6+qIlBGE70jY0BbqKNpafucQKclMktzN8+XghKGSPWmY5EwZJoXLx8jR3SvL3R7GmCGcO/S8o2+QNswZ+vVdClvuS+Vv8yLYbc2KnyfFen3iM9S+yc8wv1igr7hdfsz3Boxjeo3kr5siWTru7MnDJFfHjh1W/7iRdTq/VrxxzWzVeQgaDyHVEXUsChsh4QQL2ncibLrIY5cBu03YCYO04XbSsfjQP3yODyWd9egV8pEudOPa1ZaZ9zsigh0qu5AePRgqVrj1tGhoG7NQY1HEMdjx8Asb3u2YuHii+9PpBbtKX3a53OyUQAbQn9UqN+iLFUMIDhbi3KWj3VJnnmLt2+Rul5eK4QSVFizymCsjhtoOxvRdCJsF8lu0c4V79Nll//Q3ZNnD0ab+BJU2zBnEE/36zoTNnTv/34atKPjFYIteR5iPoNvdp5NdX41yb6HXNDvAuO0KabW7jN7xEFIdUccKr7DlDtL/yRISwRzSxbDgs57uMnP+kr1rg3yKXaMOUbK2S7Ts7BUrh95tV+5WaMrySfKFLrpj2taUqfdCWurI5u4xuvjGSYouwKn968r+N+4qdwsyLzlBZkHuHsFijYW+ruRNHeY+6wTC9uYtv5D14/5W7rPdgpK5bblMUFkbrX0ZewcWXtw+q6Migf5gtwhCoAuwCgi+h1QmfdRDjqicnm6wA4cdQszNJ3c67Uy5x9lVXN8VYqiSo2PO0fOEdsq9hk2FDfOFuVrVOVqS9HiM3XuO0UecZ3/WjXxaRqqwzdBxrdGyOCeZA1WktR3cFsScJ/aMldSZb8gJ363oqgJB3/7JYJXB2rJAx7ICt6xVgnD+MnWu0K+CaaHnB8L2j9tryCQjbM48H9SxZGmfvOPBWHCL0hsIG+YOc4GyuAaStf84FmA8KcNbycn8ij/sFkG/F2p/lz0ULZu6xcj+Z1tVuCMaFJzPHZNekzHaF9zSH9++lhl/vNa1R68PjB198Y6HkOqIOtY5CRsORiEURiUUNhLxmMVMF+iS7QsCX4cVrmz68rVywla8Yoz7rBMslpAWHIedkrkPRMkGlZbdvbAzgddLOTKR1DfO7GZ5/0TQ8aLDZmcGorNRF0cs1rhd5Q2E7e0//0Lev62GjO98uexbOtE85g1ejJ6+ZZnMeup2s8sHgUB/nF0fvA7JWXjRH7vwWiGCjEDaML7ETwdLtgofXmPnD9o4tHuDJLqviwPYiUE72FnDAg9ZwxylG2EpO1cnPa+TwviX/q2LjG9XS6apsK2GsOncoIz3HNv+nUgv25nEmyjmDW5t2sauIfq8yxU2jAtlMEZI29YesWaXbM/U143E+ucMwU5k/oEESVb5nK/1YiwQFggURHqZii52P73Clv/ZYyF/VD1390YjkJPNLUQ93uywBQtb4fRhIdcr3vWJNjEXKJugwoa+41gLhB9jzFg82ny+n1faS3LSzS8Vc5+53ZwD9HmlSmaCCitu6SaP7CE5m+aZnVDMnTd27NhVg6hB8D9WvlRZm63XO84L2oXkm7lVvOMhpDqijnXWwvZfSjlhy3kCv7kSErkcMhJUV5L6xOoCGSOL/xIlE3ShwW7FByo2kJv3bv3FOTOydQ35ROuc3cHZzUnsGSOpuqCm9McuTowRhvkqaBPvduRj1v21dcHETkmM7O8bK1m6yKOf2QrK7ekdK+vcMtjFwUI9U78u0v7Hd4uW/Tqe3ClD3SXVCUTj7ypso9rUUJHArbdapuyUeyBkeH1aLRmn9eA5gDrxOPq8pBPk0V14VYrQH/SldB6V9MdxGy7O9BnjwVzO1HFM1vpR7zi3Xnw1P7tgvnHMV9oOyqyH8LnjzhwQV9oOvkJ2MPZNOkaMdZL2D21gHjbqY8lG2OJK+2X7hvOcon3brf1frfOK+cWuHMa36MEoUx/qNTtAbnv4Pk3rwuPY7cL5mNvRme+J2mfMF+YIXzEGgMdRJ/qF4zAmyBrOCeYO9WHuUH+GO1+bujtjwThQ1xxtY5V77r3HW8rNg/YfbU6915kLlEVbGC/GbdByaXqt4bpAe0tV6jAH6D/OyWf6iwK+on3sOC7QOte55xvijPMB8Zqn84znMU47Zi8oj7HjGl6gx6Iv23TukvVcYiy2L97xEFIdgWO5rnXWwlZPscJ2c1AjhEQSWDywANrFHFKCxXOOLrRYdLAIQmjOhakKFlIsxFj0sYDt04UTt/ogXxA2yBcWUSzwaH/Fw9hhwULnCIh3kYPEHHRFD3Jjy2GR/Vq/x4IMAfULG265QR4/1cUZY8Piu1xlwoxX+4Y+Yrx4DmAO8BwEc9ujMbJXBQGLPtoPWnSt/GIureSs7lzHSBj6h4XeOy9oA49BgiCEkDy0g7IYX4avHVs/RA4yg7oxBpTFfG3XsphPlPP2y5RV0HfMC+YH84SxoTzqKRVjrR/t2DK4NoyI6nmAtGzU62O5tgVBhMjaufLOmznX+hzGDWHBLW1cW5CzUCF0zqMdC8aB84BzAsFDGbSNPoWMRX8OmgeIG64FSJxzfYXOH8QP9XkFFOUceXX6D8nE2DBGHJOkbVhwbrznE+P0jh9l8RjKQ1IxVzv1GoWs4ZzYcRMSCahjhUXYLlJaKX9K6x9bcmggfushJHLJVvTfgi7KsWaBwYK3vksdsxODBXflwypaZwnKg7W60G3oCqmIVvGBWOgipotn2uO6GPaJkR36ONrFcVist/XQ43rF6KLrHOftb5YufulaDrslkIjNKiDr3PpRxy4dQ4qOpSJh+1yFbdb9tXRRdXaWNmo5jHeN1uHtMx7D8wnaxj7tc4rbZ7Tv7Y8F85iNvmmf0T76n/BYtNM/dz7tvKxw28Fj6DeOwVgqawf14zHMHY7DXNoxb3XnC+fRCKWnnCVD5wxld+v8oD3Msz0nqA/PoX60Y8vg+0ycJ60X8425xbnBnGHOMQY7Jjt3mEeMF23gvO7RfuHaQh3e+tFPnEc7FowD5bZoOSs6aPt05yHenQt7/lG3txzKmF09fQ59suVwzdm+43xgbBgjjjmobUCC8RVtYTyb3X5inN7xoyweQ3mcD/QDY8A1bMbtGwch1Rl1rJtd14Jzwb1qKnCx0xI2HFxXaa5crfyv/o8rOaghQiINLJ5W2rDwY1GHQABIx9mD8jFmAUadkDMstFhMs7RdLGRoFwtssgoBFkUscqXHYKHz9RXgMSN8bp9RL4QC2LJ5AcL2vgrb+HY1ZV7H2kbIII8oizbxFT+jD6YfWhf6hTYwP6e74FqhsP2DgKFfSVon6sf8QgZsW3a8p9MO6rYCZetFeStElZXH497zjHIoj3pMWa03aK5NWQVlMa+QF5RH2ZDxuGPCOL31Wvn0123nyYzF7Q/OAepGGyhXaX/88+DOhS2LugPLuePAnNs2Q867Pua9/ux1Wno+9Xm05z+fKOvtf2XXLyHVGbiVOtafXNe6SKlS2MC/KT9WfqLUUOKUXypXKX+Y/0Ct2dkDYvV/ZISQLCVTFxnsxGTowoSdIpDWHzs354atC3WjDbRl28RjOOZgP8icHq/YY+1xQZi+uv1DWQvK4jm/sOE1bO/d+nMZf1cNFbZasqFLlFl0D/R12jTt6/foA8DPqNv0o4q++PHOZbpnbKg/xcW2FTLe02jHXy/Km35qHZWVx+N43s6ZHTPqQX2oN6icBWVxDPpaer484/GOyV9vZX3CMd7+4Ht7DoPKWPzzYMqadqtoU58rHYdbznvebR2o29aBr6Y979jdcqVj15/9/a+oD4RUZ9Z1jlqvjvVHpaXrXNgsg4PBxeBkcLMKhe0/lV8osUpT5Urlxr/+4acvBzVGSKSCBcYuaOeDyoQi3ORPrVjY5quw4dbVgT7OAhtUnhBCyJkDt1LHukn5jdJMgXvBwaoUtn9XIGw/V6KVxsrlyg1Km3296uRkPR6jCwkhpDqRN2WIq2pOnFuiP5cvrbB1iZLkPtFmRyWoPCGEkDMjtW/MkRY1ftRB/er3yhVKEyVGgbDBxaoUtv9QfqZEKQ2VS5XrlFvfueVnHwQ1Sgi5sMkd2z3kc75ydm+QD2/7uUxoV0MWPlBL4rtGyQEKGyGEhI1J7WtMhlspv3VdC85VR4GDwcXgZHAz62km+AYG9yMFL3L7H8W+UxR/7cC88UBpv6NHVGpQw4SQC5eDfaNlf+9os5O2oGMtmX4PPgOthsy+v6Ys71RbtnWPkhQ9Jp3CRggh5wxcqukvfvSQepV9wwFcCx/pgb809VMFLgYnK91ds7HChncjYAsOn/+BF73hXiruqWKrDrdFW9/U4N/7HugddTSzf7QQQqoHELbk3nVka7coWdGplix8oKbMuq+GLHmwlqx7pLYk9IiS1D51JK1fcHlCCCGnBxyq71U/eVGdqo1ib4fiDQdwLrxDFA4GF6tS2LAFhxe7YUsOW3ONlEsUfKgbTLDdvS3+c1hGvzpCCKkepPWtIyl9omTXo1GyuWtt2dC5lqx+qJbEd6klO7rXlr09o+QghE2PCypPCCGkapJ7RR0dev1/v6Mu1V7B56/h77X/SoFrwbnwHgI4GFwMTgY/CxE2BA/gXimMDvdOcVvUfh6bd5ftduW+9hf9+LmtXWulBXWIEHJhka4YaesdJUm9ooyg7X4sSvbpV/0fjNldwzFBZQkhhFQNnAnupA51v9Jawe4aPokDu2v289fgXnAwuJh9/Vq5eHfZsBUHw7PvFm2g2Ney4e2n2MbDOxs6v3vL/0wJ6hgh5MICQnbQ7LQ54nZAwa6buRXKnTVCCDkrknvVPgpXavCzf+3julNb5Q8K/roB7mDizQZwLTiX9wNzqxQ277tFcR8Vxof7qni7Kd7FgFujaAjSdp/ysPLYwFY/+XjmPT/fmNi9Vl563yghhBBCCIk0knrWPrapc62MRR1r7Hjh9/89rv5P/3WAetIjCnbWIGv4oFy41K8VfN4t/lAB3uhpd9fsu0PLvX7NG/8uGz4HBK9ls+8Yxa1RNGClDbdH71YeUDorjyq9lX4KOjhQGeTyJCHke+Upl6eVZ5TByhBlmPKsMlwZ4QE/Azw/VMGxKIOyqMPWB4LaI4SQSMB6DpwH7gMHggvBieBGDypwJdwGhazhdWuXKfZWKN4Zal+75n2zwWkJm30tm/3boqgIn8vmlTbcHsVr2vCiOey2oTMdlb8oMMkuSjelu9JDQccJId8vj7n0VHop+J8Ktun7KvifDOjvYn/GczgGx6IMygJbV1A7hBASKcBxAJynqwIH6qTAieBG2FW7RcFr1nAbFA4FWcPHeNg3GuCOpv0ojyp31xA86d1ls7dGvdKGNyHg9ijuu+LFcjBFdALvIMWO2x1KO+Ue5V4FW4AA923ReULI9wd2wy34rQ+/YOF/LPg8IICXOHixj+MYHIsywNYR1AYhhEQKcBsAz8HLxOA+cCC4EJwIm1o3KvgDBPjzU3An3AaFS8Gp8FcNIGv2Vijcy8papcKGWGHzSxsqhLRh6w73W/EW1OYKXtcGcYM1Xq+gY9jyg8DBKP+s4JN8wW2EkO8d/E8EYHseYIcc4LfAIOzz9nhbHgTVTwghkYL1G7gOnAfuAweCC/1OwUvIIGrYVbtIwZ/8DJI13Aq1bzSocnfNG2t2QTtteE0b3oiAdzSgUYgbtvbwLlJ0CB//cZWCW6aQOHQWu3AAhkkI+f7Bn0Kx4BctL/ifjBfvc95yQfUSQkgkYf0GrgPngfvAgeBCcCK4ERwJooaXlcGd8L4AuBScyruzdsayZmOlDRVYacP9VbwoDu9kgBmiUTSOHTd89Ac6hK0+7Ly1UNBRbP8BfDAcIeSHA3bHveB/LhXhPS6oLkIIiVSs58B54D5wILzeHy8fgxthcwuuhDuUcCf86Sm4VFhkzcbustmdNrwYzr57FGaIRnGbFDtu6Ag6hI8AgcDBJPGCOnTWgs8aIYT88MBO+ekQVJYQQiIVr+PAeeA+EDS4EJwItz7hSFbU4E5wKLiUlTXrWXaj7KxjK0Bl3t02NAY7tPKGXTds8UHg0DH8LVJ0EmAnzgvkjhBCCCHkQsTvNdZ34D5wILgQnAhuhNep2R01+7Ed/l21c5Y1myBpQ4NW3HCrFB1BhwAEDh1ERy0wS0IIIYSQ6oTXdeA+AB4EH8KmlhU1u6N23mTNG6+4WXnzCpxX4qzI+UHHCSGEEEIuZPx+Y93HyhmwbuSVNK+ondfYRiy2cb/A+bGdJoQQQgipLgQ5j/WhIEmzfKfxN27xSpwX7wAIIYQQQi5kglzHEuRHF0yCOk8IIYQQcqHDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMMwFkH/5l/8P8bZpvTzWyEsAAAAASUVORK5CYII=</file>
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    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>b={1:11:1};
c={1:10:1};
a={1:5:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[a=a*b;
ans=(a / b) + pow(c,2);
ques=join("",a," \\( \\div \\) ",b," + ",c,"<sup>2</sup>");]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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  <text></text>
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  <text>ans</text>
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  <text></text>
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  <text>_err == 0</text>
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<text><![CDATA[<h3>Simplify:&nbsp; {ques}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
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<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361121  -->
  <question type="formulas">
    <name>
      <text>L62- a(b+c+d) +f2 - p(pow(base,p)) + g / h (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{a}({b} + {c} + {d}) + {f}<sup>2</sup> - {squareRoot} + \(\frac{{g}}{{h}}\)</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"></div>
<table>
    <tbody>
        <tr>
            <td width="40%">
                <p></p>
                <p>{a}(<span class="" style="color: rgb(255, 51, 102);">{b} + {c}</span> + {d}) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; <br>{b} + {c} + {d}<br>
                <p><span>Work from left to right.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(255, 51, 102);">{b} + {c} = {=b+c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="100" height="40" role="presentation"><br><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}(<span class="" style="color: rgb(51, 102, 255);">{=b+c}</span><span class="" style="color: rgb(51, 102, 255);">&nbsp;+ {d}</span>) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>
                <p><span>Finish simplifying inside the parentheses.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(51, 102, 255);">{=b+c} + {d} = {=b+c+d}</span></span></p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>{a}(<span>{=b+c+d}</span>) + <span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2</span></sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Next Exponents from left to right<br><span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2 </span></sup><span class="" style="color: rgb(51, 255, 102);">= ({f})({f}) = {=f*f}</span><br></td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}({=b+c+d}) +&nbsp;{=f*f}&nbsp;- <span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Square roots are exponents.<br><span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> = {base}<br>because {base}<sup>{exponent}</sup>&nbsp;={factors} = {=pow(base,exponent)}</td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{a}({=b+c+d})</span> +&nbsp;{=f*f}&nbsp;- {base} + \(\frac{{g}}{{h}}\)<br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.<br><span class="" style="color: rgb(204, 51, 255);">{a}({=b+c+d}) = {=a*(b+c+d)}</span><br></td>
            <td style="text-align: center;"><br><br><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="100" height="40" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span>{=a*(b+c+d)}</span>&nbsp;+&nbsp;{=f*f}&nbsp;- {base} + <span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\)</span><br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.&nbsp;<br>Division can be show with a fraction bar.<br><span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\) = {=g/h}</span><br>
            </td>
            <td style="text-align: center;"><br><br><br></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 102, 51);">{=a*(b+c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f}</span>&nbsp;- {base} +&nbsp;<span>{=g/h}</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right.<br><span class="" style="color: rgb(255, 102, 51);">{=a*(b+c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f} =&nbsp;</span><span class="" style="color: rgb(255, 102, 51);">{=a*(b+c+d) + (f*f)}</span><br></td>
            <td><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(51, 204, 255);">{=(a*(b+c+d))+(f*f)}</span><span class="" style="color: rgb(51, 204, 255);">&nbsp;- {base}</span> +&nbsp;<span>{=g/h}</span>

            </td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(51, 204, 255);">{=(a*(b+c+d))+(f*f)} - {base} = {=(a*(b+c+d))+(f*f) -base}</span></td>
            <td><br></td>
        </tr>

        <tr>
            <td><span class="" style="color: rgb(70, 255, 150);">{=(a*(b+c+d))+(f*f)-base} + {=g/h}&nbsp;</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(70, 255, 150);">{=(a*(b+c+d))+(f*f)-base} + {=g/h} = {=(a*(b+c+d))+(f*f)-base + g/h}</span><br></td>
            <td><br></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={-3,-2,-1,2,3,4};
b={-10:-1,2:10};
c={-10:-1,2:10};
d={-10:-1,2:10};
f={2:12:1};
g={-5:-1,1:5};
h={-5:-1,1:5};
pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};
</text>
</varsrandom>
<varsglobal><text><![CDATA[g=g*h;
base=pair[0];
exponent=pair[1];
squareRoot=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}
ans=a*(b+c+d) +pow(f,2) - base + g / h;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 361120  -->
  <question type="formulas">
    <name>
      <text>L62- a(b-c+d) +f2 - p(pow(base,p)) + g / h</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{a}({b} - {c} + {d}) + {f}<sup>2</sup> - {squareRoot} + \(\frac{{g}}{{h}}\)</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"></div>
<table>
    <tbody>
        <tr>
            <td width="40%">
                <p></p>
                <p>{a}(<span class="" style="color: rgb(255, 51, 102);">{b} - {c}</span> + {d}) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; <br>{b} - {c} + {d}<br>
                <p><span>Work from left to right.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(255, 51, 102);">{b} - {c} = {=b-c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="100" height="40" role="presentation"><br><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}(<span class="" style="color: rgb(51, 102, 255);">{=b-c}</span><span class="" style="color: rgb(51, 102, 255);">&nbsp;+ {d}</span>) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>
                <p><span>Finish simplifying inside the parentheses.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(51, 102, 255);">{=b-c} + {d} = {=b-c+d}</span></span></p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>{a}(<span>{=b-c+d}</span>) + <span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2</span></sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Next Exponents from left to right<br><span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2 </span></sup><span class="" style="color: rgb(51, 255, 102);">= ({f})({f}) = {=f*f}</span><br></td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}({=b-c+d}) +&nbsp;{=f*f}&nbsp;- <span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Square roots are exponents.<br><span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> = {base}<br>because {base}<sup>{exponent}</sup>&nbsp;={factors} = {=pow(base,exponent)}</td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d})</span> +&nbsp;{=f*f}&nbsp;- {base} + \(\frac{{g}}{{h}}\)<br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.<br><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d}) = {=a*(b-c+d)}</span><br></td>
            <td style="text-align: center;"><br><br><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="100" height="40" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span>{=a*(b-c+d)}</span>&nbsp;+&nbsp;{=f*f}&nbsp;- {base} + <span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\)</span><br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.&nbsp;<br>Division can be show with a fraction bar.<br><span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\) = {=g/h}</span><br>
            </td>
            <td style="text-align: center;"><br><br><br></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f}</span>&nbsp;- {base} +&nbsp;<span>{=g/h}</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right.<br><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f} =&nbsp;</span><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d) + (f*f)}</span><br></td>
            <td><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)}</span><span class="" style="color: rgb(51, 204, 255);">&nbsp;- {base}</span> +&nbsp;<span>{=g/h}</span>

            </td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)} - {base} = {=(a*(b-c+d))+(f*f) -base}</span></td>
            <td><br></td>
        </tr>

        <tr>
            <td><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} + {=g/h}&nbsp;</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} + {=g/h} = {=(a*(b-c+d))+(f*f)-base + g/h}</span><br></td>
            <td><br></td>
        </tr>
    </tbody>
</table><br>]]></text>
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gjV+UFbRhB9NTr/0WhePtC2aHjyfykj5wqyHQfrTjH0nfKXr1W9g9wznnOM01NOzg/3+wK3VE7k2zv7cxpip5z1FngXn/+26oVBfN8aN7fQ85nAfpV2RwTUs1Qx6KwERJOKhO2vPQkefPWKHnn9ij5sG0dGX1XtIxtFy2fqYR9dnflfK58oUzrGCfzH6on8Y81NJIAAbPyZcRtVIdyclNycKesVMHDwglRQhmz0+EueKdSN7tHOjmStlOWdK4nq7vXNzt5WCgP6UJbMut59wgnByYMl33jh5sF9UyS/tU7RiQgIKjXCqR/LiFr/yysWjSCgj4ljeplhBLtYJHP03as3KJ+fPWL07onr5UTeRnuT6eXg7Pfli29nHmCQB/G7pynHS8nv37vjOTTBn1KHPZbI7tpKi1owy+G/usub+tCSVs81v3p9HJc28E5393fkSO0A8E6sfZz94gzy7HDGaXXEs6FEUGtEzuxZxL0a/2jDUwdED9nx7EKMSakGqGOFV5hKxmGf0CERC7YjTj6VajY2EDY3r4tSt5rHSVjVNa+vDdGptwfKzNUwmY+UDWzlEUP15WVXevLjt4NdeFubHYsij1tFwxpKkfip7stlmX7p8NkeZd6Km0qegMay2EjSk3luG+Rh+gsH9DK9GnJI/XMIrmnfyNH8mY95x7lpGBfvPtdWbCwHtq0QLLiF0je3ng5dby8nJzSNtYMukals4FKTiPJ0EUc/Ub/S+fyjd/LtxXI2pGs/ZIZP18ywMb5Upy5330mNGgn4cOeshFj6NdI0p7QcQ/GDg8k15mvb3NDdwZRxhvMB8aZrWPK2bFCThTnuc+UBWVWDGwl63vUNztJB7WdPG3HEaoyjk7o55YoC+o/nLBS9kx7y5yjbZ8MldSVU6QkYEwY92oj3pD1xpL9VBMp9Mzb0dmh151/LAjOD8aSqeenMCXRfTQ0OH/YwUU7qToWtINrpXDmc5I7bYSkThxe7txn7tooKz4aLKtGDpH1o4fI5rFDZauOZeXzd8mCh+qWXnuYm5LF77qlylKcmigHFo6RbZ8ONexfMLpc/xY/UlfWqPgl9m1orplcXPs6dnv9E1KdUceisBESTqoSNsjaqDvryGQVtYUqX1jI1ulCj8V+g4pFVWzt1dAsWFiwDz2tC6mKgbdtyAgWxROHQkXkeFGeLOzXysgeymMRznv1hnKvBzuosjDpvlizmzfnL3GyVhdIyA7EsEgX7Ipy9HCGWaAhoBNURMe5O4LTH2spObs3ukeVJXdPvCzW8W/u2UD2q7Rh8bUihQXYf2sXyVdJmNWzpdltxM7kp+2j5XMF7cyooB30C8KAucM4zLh1ztAGhMovbN6kbZhv5gLjGX9P2ZiC2klePlnmdaprzqMVXEiOPTcQUP9cFyZtknl9rjb1YxyoH+3g54na7qYxQ8sJ7/4FY2RF13qyo09DSdFrwCuGR3zC5g3mYe3bj5rx4BcFjAOsfLOHfONrA21C2CFtVkAhutjZ26tjw/UK6fMmae08eVev7Q/a1DG/jGAcaGtqh1iZq9fR0s719NptYATwZMZOt5STjFVTTJ8w/s8wD+4cgCXP3mmulXyVtxkdY825hOhbYcU1T2EjkYA6VniFrXgofuMhJHLBjsfR2cFiA2H7sE2UWZTmdYqT+Efry06Vp5SBjSRVwcJYFemDGkvWk40lx8ias8Ni2y7S7/Fzpj6f/Wlvt9WypG+cbyQMUpGkknR0x0L3GSfYwflSF8uJulBOvi9Glj5SV7bpIntgQCM5/IwujhUI2yEVGAiHs2Oo8qQL61cPOgv1fB0n2gzaMVqgsmLbwO4XxlSk4wgS3qz4+aZPmLvx90Sb79GObWOhLuSY0/y95Xf99s0fbY7ZoPONcWN+IIeYvyBhg8CsHjlYPmlXx2mrdExxpg206R9PYUaSGTt2QCGhOFcQaowH5+SbnaGvicOO0swHVJ6M2MTINBUb1I/yS3ROvu5c13yfsnCMW8IJ3niC+Vyl0pao0oax4Nzg/Jf4dkBtsvX8TO5xlYqQM2/Tta3ZnvOT8NlQ98iybBw9xDy3Uedsb/+GckjlKEOvPVynCX0aSN7WUGFLXjdPPmqLnWP8MhKjYqWSpuNYob+Q4HrbonOCejK0v/5g7J+qgGMuMIdzdB4wBwB12HMLwccvOBA//JsxwqZzizm2/wYIqa6oY1HYCAknVQnbP3RR++LuaLMYb+/t7C5lP6WLuy4+EJaqyFWwQFtZ8y9W+BnHYHEt2hYqZMjqt3qYhTB1dC/3ESe4fbZsxF1mwcXOxiyVibXd64UITnGAEGTt2mgk9KO2dYy0YcHFQr9ShQIL9ebHnN3D3R/1dEuUZdfc0TJdRWhNt7J2MKZTmaE7MBBJ1P2JLuqj76xjBAcLOBZvCAXagPTF69d13evLSd9ty7wDic5ujY57uyugeTp/wC9skLUFr3aTv99WW0be4YwJfYQsQJIg2Rt0POmz33ZLlAUyiR0lHLevf9l4MHf+3bU5vVsaGYSooMxCFZzVOg9bVWx26HUBGTNj0vb841ky/E4jWxh7qbjoeQ8StsydG+X91lHmHGFHEjKFufOeH5xn3Cr15oAKGM4lxBH9wS8J5jrVawvSVrI99NrC8RBcSBdkDf3G9b27X0NzbtFPyBquYX/w72GUzjXOK64dzAPOE9pNUCDA6CvA3OOXHK8Qe69/Qqor6ljhFbaiIfiNh5DIpUAl4EgFOx15aUlmFwIL9dcqD7v6YmepkSlTGFDX2ZL3DASwsezVxfJkfuhCjJ2gmR1jyi3QeE3YhHshEHVkhj6P/m3rVd/0D3UVah+LfTts2O1573YVGx0TFuvpHSBFcbJeBSBRF9o9/SCkDc3XxD4Nyr2YP2PbcjMXSx6OMwtzCkRK++5P0vzRRtQ+bw+ZjDaLOtrYrv3b17+haSN5QEPz/W6d08PrprolyzJWRXQ2JFRlAMdgTLlPN5ZTPmHb+/Uk+YfKzQeta8sXKjgQ12UqLRAbjCFJ28C87h9+nVuiLI6wRMtSnQMce1AlBWJdPL6Pe4STotREM5ZxKio4ft5fHGnd2hO3nxuUjgnf79R6ivdvcks6we4XZGpFl7rmmHT3GvKfH9wGH/vwFeaaw/in4fzoXPvPD67D4l0r3VJOIGB2rjF2XAfZKlyH9fxA3vy7syl6/Gc6pkn3RZv5snOFchmDnLI5Ot/4ZQMf2eHNrrkfy8d3RMlUHRPmDrKHOUjWvqXoebVzYcFj6MNhrS/o+iekOqKORWEjJJz8EIQNcgVRwEJ+aOpwt/WyFGWE3s7D65sgENjpgEQs0EV6ky7SWHCxyObjdqjWW+ITgiKVPwjbGJUpLO6LVAa2qHRgsc16spHkqBRBwPAVPx/ZHSoFkEeI2JwHY3WRrmfaC9olQp/svBnpUuFAG5g7SBckAu3ge4hY5rv3uCXLsuqjwUYmICwQPfQHx/qFbc3IwTJK5QFAcCBFEFfsKqEM2sKcYLfJn3UfDzHSBsmBfEEi0a8TiaG3Qw/vjTftQLzwJoN944ZJ5uThkjN1hBTMcCh0v+ZPHyFHk0OF7eD6eeZ8LXooTnZo3yC6ON/+W9Y4P+/q+cEcQwxxfND5gUz5BawgPcnM+8yOsbK+Rz0zfowZ1ymuB/+YUrRPOD+QdkjxAVeqzLXtXt8AP/vbQlAevyis6urIXqZKHs4P+gcxw5zjZ/QB5xmPoy7/tU9IdUUdK7zCVjgYv4kTErnk60JyZNYIdxkKDYTtH21q60JYR5aqOOzsU18ODmxoyhQE1HW2oK4CsxA3klRdOP27J/6sfLO7jL0rSibogovdNyyau9y+HX5aZUDrQr3FM0PHBSF4v3VtIw8zdKFGOexepWq5nKdUbtyy+Iqfj/gWauwAYXcOZVdrWczHsU3T3GedQCY/Uwka2ba2THaFa+tj9UzfMD4s3GgDOIt7I0nT5/xZqcI2Xud9riuHOCZLpSBI2MbcGWXaxM7XJj12b78G5liMwY4nV7/3Z93HTtk5D8aYckn9G5hjT6aECte5JlXlBucL/dusc5H8eAPJU4kpCjo/KmwYC0Rqlcpn0PnB98cTygsbzuvU+6PNudmvY4FE4dpCWycSfTtsEDad32l6/NpudeXA4878mmtR8V6XWS/9Vv4Z8A5WvNkhN2GFJPytnbkW0Gb6Ew1NuzjX6Cfm3fbb1ktIJKCORWEjJJxgIfm+hc2ChfWQLnDJI66Tb0rKfxwFgltfkCbckpqii60Rop6O0BzSRdLbryBh+1DHA9Fb0MmRh6By+N6McUb5ecF8TMFttEecna9jPnFAG5AT7HhBJiEDe1Q6sHhD0GwbXjBm/wfF4kXxVizXaR24rZY5qGGgsH2ugjPx3mhZ3jnOtAVp8J4jOx5/1quwYR6/eiBGNvaoJ/tU9HJVLk7nQ4XPJDhn3nasGBb55rfs/GDXT8+PK6r+84N59AsYhA2ih3lYofMAac3QeUC5oOOtsDk7bM78QrJsGxaUNwL2Sa8Kr0nkWPZ+yV021owN/0awIwhZO1//Vgj5oaOORWEjJJxgQfmhCBvqxUKOxdN/W81mw/jXzO7VJypFEADIzO6+zi1DlPXWFyRsGM8kXdQXPxRrRA+LOmTKWw6Y8QUIG4TClHd3zo75duFw2xS7VqOVUhFyBQXj87cDsLDjz2F5A2GDgNgdI+xKQcT8x0HYvlCxg0Rix9C7s2Trx/do2x8IG8RytvZzg/YTkoO+hFPYsCs5Z3AbM5b57g4b+liRsNnzs6iS81ORsH3aLkq+VNmDTGNnLg3CpsdWtsNWlbABCDXEcefQayV384LAz4uzgdRlfvW27Ozt7Lih/xBO82+mgvNPSHVEHSu8wlbwjP6PjZAIJk8XzhKf2NhA2CAo49pHyZKHY3URqiepA3A7CwtQcH3nCurN/7z8R3zYHCs8LF90uUIlJUoWdYqV7bqoH1CZyX2qoemXt66KhGDyvXXMeLZp2UwjBFjYQ8sGlUc+aF1LvtSFfv5fYiS+R91yr29yhA2vk4uSuQ/GyOZHIVH1HWHz9c+Cvvt32LbPHmWkdKL21ewYqZQe1LkPErZxKmzm1l7XODMXWYNCx4M5xdz4g1uikN+ZHaON+O7RNg492bCcsOEF+m/9uaa8d3stM3+j78BtS9yGjZLPA8Djn2rfx+ocfOweC5EykqzClqwigzH7hfh0zw/GEiRs2NkMulYPq3CVEzYdU1XzZkH5bJ2Xff3qyyY9n6sHXC0pKyabN7FUlMNbFsgWPdact4HYYS1/fRJSnVHHorAREk6wiPxQhM3Imtbtlxf/B6WmbVluJGCBStMWs2NT/7wIm/91UihvhE3lA21j8Q4SNgjNmQqbP3jTAaRn0vcgbP4Pik3fulzeubWWORZCNvk+vIM1xuwgYox+8Jq4Oe7zs7XueTpXkLUN3Z020lRg0J+zPT8o+10KG+rAOUK/cR5wTpd3jjXSvuGd7nJ4T/kPJkaSZ7wpa7vFSUIvpy+oH9fA+fi3Q8gPDXWs8Apb/tP4B0RI5HJYF6KSmeXfmYkYYVNBwW7W4odiJFEXnpTHVT60TF5AXecK6vQvrMWZSZL09ST3p7KsGzVY5SBa4nvEyb6+9VQ0Gph+eesrmhE6LiMEOh5IEMaz9bG6kqGLMMp6y1n8L77PO5Ag79+OHTZHFtF2wYLyn2+GXSVI25wHomWTHpPUzxVKX/8sBR/e7ZYsy4ynWquw1ZZJKofLH4lV0dFFX+c++JZolExViVrTNVaSVQ4znwgdD+YVc+MP5nBkm1oyswOELU5296kn2YMaqISGfsgsJPTd22rKJ9oftIOxr+oSa9pDucpYr2CesNuE+jGGLO0f+nS25wdjORHwpoOxd+KjTcpfq7kqof7jIWxVzZsX9DdH+4G+41jUv6F7nHytcojrcN3b3cvtuB3Vn7/SawD1m7EPqPw6IKQ6oY5FYSMknGBB+6EIW9G48rdCFw1rYxZiLMjelOSmyzRdbJepzGzThf2gLoaQDW+//EKABRXjmXBPlCzs5Ox+pbnlvP0AqOfbI6EvMse7HbHDBolaovMBCTn0bnnZ2jzhdfm4bW2zu4RFfa/KFhZ7zJu/HeB/p+mJojzTT+wiQihWqxxB+tDX70LYCn0Sih1O3A5FOxjTys64FV3XXA8oUxF7XCDU+7X/OEcQHswF+nUhCRtAXeg7+oS6MTbMA87xCp2Tbe/1cGsvC+R+oSv3uA4wv5C2oPoJqU6oY4VX2PKe0v/BExLB5OoCVOxbOG0gbB/cXlM+b1dbFnWK1sUpTpL71ZNDg+pLDhYeLXumHAYB/QDfFvg+HHfjPBlzRy0ZrSx9rav7aFnSNsyTWR10wVWh2dvXkS/Thltf4fTy48ratUHGt68t8x6Mlo3dYyWlfz3JHIiFvawf+P7Yqk/cEmX5WvvwYeuaMuXeKFn2cIyKYpwjUb53DxaqPECEZtzv9G1X77oqKjpn2jfbhqXglevKiWHWtuXyvjvvqGMthELn3RG20M+kWzPyGflCj5t6X5QRu/16XIaOx9sGxoN58Wetlv3I7SfasP3MeP4a94iybJ810t1ZjJZ4FZQDOm/p2p9svRaqAteLuWa0D5WdHwgb5neiCvVivd62PhpX2oZ3PKjjeELoLiCEDdcK5gxlE1Sk0Ecci2vVf3zKurlVzltF4BrGWDBX6B/OzW6dO1xP/mB+0QauF/z7QRuYi6B6CalOqGNR2AgJJ1jQqhK2z+6qLQt1oYagJOnihIUqG+jCc7pUtGgDLIDHfbtM+PNGWLixCI9TwcKiB4HzZ/Wb3YxMbnZvjXrFKEjYEPwtUezOrXgkRnb2chZ2jMdK6OGXry0nUXi3I8TRK2IoC9k7sj1UBpDts0fKJFc80LeUxx0hsOO3IhH0mWfzB7eRD3XeIUgQS+zOpLrlz7ewYR4ghscPhPYLu2zTe1whM1WQ0c6ePnVNn3C8Oa86FmDPM8553vt3S/aL15r+YJ7MHGN+laDz810KG3ZocV3jHOE6wHgOPu4Iv8X+cmHqUOy4StHxWGnD+d03rJVbuxPMGcZjrwOMB3PrHw8h1RF1rPAK2+En9TdrQiKYHF08/LemzkcOz31L9uqieKBfXV3gIFZYTJ0+FHxwt/zzZOgbC+JHD9YFtZaMblvL7GhhwVsz4Kpyf6cSu1nTVFaWPxIt27HjpQsn6ka9hdOedY8qH8jB+hfaml2RXb2ccpkD6xnJOOXb6UN2qICNalPT9OerjnVMOSzyaCttRCv5NuCjHg6unysL+1wpqzvHyO7e2JWC4Dn9QzvfZCS6R5YFfxUAYugs9LVl6UMqyo/GmjlDWb+wrf7oaflc5wlztErbSerrzK/3HGOecZ79gbD9Q9uZrvO3pkuMmQf0DeWz/97ePaosR1Ry1rzZ1fRph871fm0LfXJk1wFSg+vJiiheD5eq4gQyUK97bND5wTnBLwgT764ti/QXhC09YkPOpwXlg4QN84a5QFn0D9ea6ZO2WbKw/GsN1496xuy2YjyJZve4rp6X9trHMhE9umqsuTaP6ziyX7jG9MeeC/TLCKoei+OPHwj9Q/7mNY+31XR2dB+oI/F6zWAeUNY7HkKqI+pYFDZCwgkWtO9C2EqS4s2ChYVxvyttaDtH++CXkMKUBPnkTmfx/VIXu/kP1pEN3WJN+cyv3nSPKsuBZZOMRK1V6XB2Spy6CyoRNpsjWUmSt2W+FG6dL8fTygsUYkVirAoB+rNE5RFCgAUeizUW8fx5b7lHhwafhl+UmmDaKNA2irctkBOHQsdrg7+SACHEThHGjzGt6+qIlBGE70jY0BbqKNpafucQKclMktzN8+XghKGSPWmY5EwZJoXLx8jR3SvL3R7GmCGcO/S8o2+QNswZ+vVdClvuS+Vv8yLYbc2KnyfFen3iM9S+yc8wv1igr7hdfsz3Boxjeo3kr5siWTru7MnDJFfHjh1W/7iRdTq/VrxxzWzVeQgaDyHVEXUsChsh4QQL2ncibLrIY5cBu03YCYO04XbSsfjQP3yODyWd9egV8pEudOPa1ZaZ9zsigh0qu5AePRgqVrj1tGhoG7NQY1HEMdjx8Asb3u2YuHii+9PpBbtKX3a53OyUQAbQn9UqN+iLFUMIDhbi3KWj3VJnnmLt2+Rul5eK4QSVFizymCsjhtoOxvRdCJsF8lu0c4V79Nll//Q3ZNnD0ab+BJU2zBnEE/36zoTNnTv/34atKPjFYIteR5iPoNvdp5NdX41yb6HXNDvAuO0KabW7jN7xEFIdUccKr7DlDtL/yRISwRzSxbDgs57uMnP+kr1rg3yKXaMOUbK2S7Ts7BUrh95tV+5WaMrySfKFLrpj2taUqfdCWurI5u4xuvjGSYouwKn968r+N+4qdwsyLzlBZkHuHsFijYW+ruRNHeY+6wTC9uYtv5D14/5W7rPdgpK5bblMUFkbrX0ZewcWXtw+q6Migf5gtwhCoAuwCgi+h1QmfdRDjqicnm6wA4cdQszNJ3c67Uy5x9lVXN8VYqiSo2PO0fOEdsq9hk2FDfOFuVrVOVqS9HiM3XuO0UecZ3/WjXxaRqqwzdBxrdGyOCeZA1WktR3cFsScJ/aMldSZb8gJ363oqgJB3/7JYJXB2rJAx7ICt6xVgnD+MnWu0K+CaaHnB8L2j9tryCQjbM48H9SxZGmfvOPBWHCL0hsIG+YOc4GyuAaStf84FmA8KcNbycn8ij/sFkG/F2p/lz0ULZu6xcj+Z1tVuCMaFJzPHZNekzHaF9zSH9++lhl/vNa1R68PjB198Y6HkOqIOtY5CRsORiEURiUUNhLxmMVMF+iS7QsCX4cVrmz68rVywla8Yoz7rBMslpAWHIedkrkPRMkGlZbdvbAzgddLOTKR1DfO7GZ5/0TQ8aLDZmcGorNRF0cs1rhd5Q2E7e0//0Lev62GjO98uexbOtE85g1ejJ6+ZZnMeup2s8sHgUB/nF0fvA7JWXjRH7vwWiGCjEDaML7ETwdLtgofXmPnD9o4tHuDJLqviwPYiUE72FnDAg9ZwxylG2EpO1cnPa+TwviX/q2LjG9XS6apsK2GsOncoIz3HNv+nUgv25nEmyjmDW5t2sauIfq8yxU2jAtlMEZI29YesWaXbM/U143E+ucMwU5k/oEESVb5nK/1YiwQFggURHqZii52P73Clv/ZYyF/VD1390YjkJPNLUQ93uywBQtb4fRhIdcr3vWJNjEXKJugwoa+41gLhB9jzFg82ny+n1faS3LSzS8Vc5+53ZwD9HmlSmaCCitu6SaP7CE5m+aZnVDMnTd27NhVg6hB8D9WvlRZm63XO84L2oXkm7lVvOMhpDqijnXWwvZfSjlhy3kCv7kSErkcMhJUV5L6xOoCGSOL/xIlE3ShwW7FByo2kJv3bv3FOTOydQ35ROuc3cHZzUnsGSOpuqCm9McuTowRhvkqaBPvduRj1v21dcHETkmM7O8bK1m6yKOf2QrK7ekdK+vcMtjFwUI9U78u0v7Hd4uW/Tqe3ClD3SXVCUTj7ypso9rUUJHArbdapuyUeyBkeH1aLRmn9eA5gDrxOPq8pBPk0V14VYrQH/SldB6V9MdxGy7O9BnjwVzO1HFM1vpR7zi3Xnw1P7tgvnHMV9oOyqyH8LnjzhwQV9oOvkJ2MPZNOkaMdZL2D21gHjbqY8lG2OJK+2X7hvOcon3brf1frfOK+cWuHMa36MEoUx/qNTtAbnv4Pk3rwuPY7cL5mNvRme+J2mfMF+YIXzEGgMdRJ/qF4zAmyBrOCeYO9WHuUH+GO1+bujtjwThQ1xxtY5V77r3HW8rNg/YfbU6915kLlEVbGC/GbdByaXqt4bpAe0tV6jAH6D/OyWf6iwK+on3sOC7QOte55xvijPMB8Zqn84znMU47Zi8oj7HjGl6gx6Iv23TukvVcYiy2L97xEFIdgWO5rnXWwlZPscJ2c1AjhEQSWDywANrFHFKCxXOOLrRYdLAIQmjOhakKFlIsxFj0sYDt04UTt/ogXxA2yBcWUSzwaH/Fw9hhwULnCIh3kYPEHHRFD3Jjy2GR/Vq/x4IMAfULG265QR4/1cUZY8Piu1xlwoxX+4Y+Yrx4DmAO8BwEc9ujMbJXBQGLPtoPWnSt/GIureSs7lzHSBj6h4XeOy9oA49BgiCEkDy0g7IYX4avHVs/RA4yg7oxBpTFfG3XsphPlPP2y5RV0HfMC+YH84SxoTzqKRVjrR/t2DK4NoyI6nmAtGzU62O5tgVBhMjaufLOmznX+hzGDWHBLW1cW5CzUCF0zqMdC8aB84BzAsFDGbSNPoWMRX8OmgeIG64FSJxzfYXOH8QP9XkFFOUceXX6D8nE2DBGHJOkbVhwbrznE+P0jh9l8RjKQ1IxVzv1GoWs4ZzYcRMSCahjhUXYLlJaKX9K6x9bcmggfushJHLJVvTfgi7KsWaBwYK3vksdsxODBXflwypaZwnKg7W60G3oCqmIVvGBWOgipotn2uO6GPaJkR36ONrFcVist/XQ43rF6KLrHOftb5YufulaDrslkIjNKiDr3PpRxy4dQ4qOpSJh+1yFbdb9tXRRdXaWNmo5jHeN1uHtMx7D8wnaxj7tc4rbZ7Tv7Y8F85iNvmmf0T76n/BYtNM/dz7tvKxw28Fj6DeOwVgqawf14zHMHY7DXNoxb3XnC+fRCKWnnCVD5wxld+v8oD3Msz0nqA/PoX60Y8vg+0ycJ60X8425xbnBnGHOMQY7Jjt3mEeMF23gvO7RfuHaQh3e+tFPnEc7FowD5bZoOSs6aPt05yHenQt7/lG3txzKmF09fQ59suVwzdm+43xgbBgjjjmobUCC8RVtYTyb3X5inN7xoyweQ3mcD/QDY8A1bMbtGwch1Rl1rJtd14Jzwb1qKnCx0xI2HFxXaa5crfyv/o8rOaghQiINLJ5W2rDwY1GHQABIx9mD8jFmAUadkDMstFhMs7RdLGRoFwtssgoBFkUscqXHYKHz9RXgMSN8bp9RL4QC2LJ5AcL2vgrb+HY1ZV7H2kbIII8oizbxFT+jD6YfWhf6hTYwP6e74FqhsP2DgKFfSVon6sf8QgZsW3a8p9MO6rYCZetFeStElZXH497zjHIoj3pMWa03aK5NWQVlMa+QF5RH2ZDxuGPCOL31Wvn0123nyYzF7Q/OAepGGyhXaX/88+DOhS2LugPLuePAnNs2Q867Pua9/ux1Wno+9Xm05z+fKOvtf2XXLyHVGbiVOtafXNe6SKlS2MC/KT9WfqLUUOKUXypXKX+Y/0Ct2dkDYvV/ZISQLCVTFxnsxGTowoSdIpDWHzs354atC3WjDbRl28RjOOZgP8icHq/YY+1xQZi+uv1DWQvK4jm/sOE1bO/d+nMZf1cNFbZasqFLlFl0D/R12jTt6/foA8DPqNv0o4q++PHOZbpnbKg/xcW2FTLe02jHXy/Km35qHZWVx+N43s6ZHTPqQX2oN6icBWVxDPpaer484/GOyV9vZX3CMd7+4Ht7DoPKWPzzYMqadqtoU58rHYdbznvebR2o29aBr6Y979jdcqVj15/9/a+oD4RUZ9Z1jlqvjvVHpaXrXNgsg4PBxeBkcLMKhe0/lV8osUpT5Urlxr/+4acvBzVGSKSCBcYuaOeDyoQi3ORPrVjY5quw4dbVgT7OAhtUnhBCyJkDt1LHukn5jdJMgXvBwaoUtn9XIGw/V6KVxsrlyg1Km3296uRkPR6jCwkhpDqRN2WIq2pOnFuiP5cvrbB1iZLkPtFmRyWoPCGEkDMjtW/MkRY1ftRB/er3yhVKEyVGgbDBxaoUtv9QfqZEKQ2VS5XrlFvfueVnHwQ1Sgi5sMkd2z3kc75ydm+QD2/7uUxoV0MWPlBL4rtGyQEKGyGEhI1J7WtMhlspv3VdC85VR4GDwcXgZHAz62km+AYG9yMFL3L7H8W+UxR/7cC88UBpv6NHVGpQw4SQC5eDfaNlf+9os5O2oGMtmX4PPgOthsy+v6Ys71RbtnWPkhQ9Jp3CRggh5wxcqukvfvSQepV9wwFcCx/pgb809VMFLgYnK91ds7HChncjYAsOn/+BF73hXiruqWKrDrdFW9/U4N/7HugddTSzf7QQQqoHELbk3nVka7coWdGplix8oKbMuq+GLHmwlqx7pLYk9IiS1D51JK1fcHlCCCGnBxyq71U/eVGdqo1ib4fiDQdwLrxDFA4GF6tS2LAFhxe7YUsOW3ONlEsUfKgbTLDdvS3+c1hGvzpCCKkepPWtIyl9omTXo1GyuWtt2dC5lqx+qJbEd6klO7rXlr09o+QghE2PCypPCCGkapJ7RR0dev1/v6Mu1V7B56/h77X/SoFrwbnwHgI4GFwMTgY/CxE2BA/gXimMDvdOcVvUfh6bd5ftduW+9hf9+LmtXWulBXWIEHJhka4YaesdJUm9ooyg7X4sSvbpV/0fjNldwzFBZQkhhFQNnAnupA51v9Jawe4aPokDu2v289fgXnAwuJh9/Vq5eHfZsBUHw7PvFm2g2Ney4e2n2MbDOxs6v3vL/0wJ6hgh5MICQnbQ7LQ54nZAwa6buRXKnTVCCDkrknvVPgpXavCzf+3julNb5Q8K/roB7mDizQZwLTiX9wNzqxQ277tFcR8Vxof7qni7Kd7FgFujaAjSdp/ysPLYwFY/+XjmPT/fmNi9Vl563yghhBBCCIk0knrWPrapc62MRR1r7Hjh9/89rv5P/3WAetIjCnbWIGv4oFy41K8VfN4t/lAB3uhpd9fsu0PLvX7NG/8uGz4HBK9ls+8Yxa1RNGClDbdH71YeUDorjyq9lX4KOjhQGeTyJCHke+Upl6eVZ5TByhBlmPKsMlwZ4QE/Azw/VMGxKIOyqMPWB4LaI4SQSMB6DpwH7gMHggvBieBGDypwJdwGhazhdWuXKfZWKN4Zal+75n2zwWkJm30tm/3boqgIn8vmlTbcHsVr2vCiOey2oTMdlb8oMMkuSjelu9JDQccJId8vj7n0VHop+J8Ktun7KvifDOjvYn/GczgGx6IMygJbV1A7hBASKcBxAJynqwIH6qTAieBG2FW7RcFr1nAbFA4FWcPHeNg3GuCOpv0ojyp31xA86d1ls7dGvdKGNyHg9ijuu+LFcjBFdALvIMWO2x1KO+Ue5V4FW4AA923ReULI9wd2wy34rQ+/YOF/LPg8IICXOHixj+MYHIsywNYR1AYhhEQKcBsAz8HLxOA+cCC4EJwIm1o3KvgDBPjzU3An3AaFS8Gp8FcNIGv2Vijcy8papcKGWGHzSxsqhLRh6w73W/EW1OYKXtcGcYM1Xq+gY9jyg8DBKP+s4JN8wW2EkO8d/E8EYHseYIcc4LfAIOzz9nhbHgTVTwghkYL1G7gOnAfuAweCC/1OwUvIIGrYVbtIwZ/8DJI13Aq1bzSocnfNG2t2QTtteE0b3oiAdzSgUYgbtvbwLlJ0CB//cZWCW6aQOHQWu3AAhkkI+f7Bn0Kx4BctL/ifjBfvc95yQfUSQkgkYf0GrgPngfvAgeBCcCK4ERwJooaXlcGd8L4AuBScyruzdsayZmOlDRVYacP9VbwoDu9kgBmiUTSOHTd89Ac6hK0+7Ly1UNBRbP8BfDAcIeSHA3bHveB/LhXhPS6oLkIIiVSs58B54D5wILzeHy8fgxthcwuuhDuUcCf86Sm4VFhkzcbustmdNrwYzr57FGaIRnGbFDtu6Ag6hI8AgcDBJPGCOnTWgs8aIYT88MBO+ekQVJYQQiIVr+PAeeA+EDS4EJwItz7hSFbU4E5wKLiUlTXrWXaj7KxjK0Bl3t02NAY7tPKGXTds8UHg0DH8LVJ0EmAnzgvkjhBCCCHkQsTvNdZ34D5wILgQnAhuhNep2R01+7Ed/l21c5Y1myBpQ4NW3HCrFB1BhwAEDh1ERy0wS0IIIYSQ6oTXdeA+AB4EH8KmlhU1u6N23mTNG6+4WXnzCpxX4qzI+UHHCSGEEEIuZPx+Y93HyhmwbuSVNK+ondfYRiy2cb/A+bGdJoQQQgipLgQ5j/WhIEmzfKfxN27xSpwX7wAIIYQQQi5kglzHEuRHF0yCOk8IIYQQcqHDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMAzDMMwFkH/5l/8P8bZpvTzWyEsAAAAASUVORK5CYII=</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={-3,-2,-1,2,3,4};
b={-10:-1,2:10};
c={-10:-1,2:10};
d={-10:-1,2:10};
f={2:12:1};
g={-5:-1,1:5};
h={-5:-1,1:5};
pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};
</text>
</varsrandom>
<varsglobal><text><![CDATA[g=g*h;
base=pair[0];
exponent=pair[1];
squareRoot=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}
ans=a*(b-c+d) +pow(f,2) - base + g / h;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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<text></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 361122  -->
  <question type="formulas">
    <name>
      <text>L62- a(b-c+d) +f2 - p(pow(base,p)) - g / h (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{a}({b} - {c} + {d}) + {f}<sup>2</sup> - {squareRoot} - \(\frac{{g}}{{h}}\)</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"></div>
<table>
    <tbody>
        <tr>
            <td width="40%">
                <p></p>
                <p>{a}(<span class="" style="color: rgb(255, 51, 102);">{b} - {c}</span> + {d}) + {f}<sup>2</sup>&nbsp;- {squareRoot} - \(\frac{{g}}{{h}}\)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; <br>{b} - {c} + {d}<br>
                <p><span>Work from left to right.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(255, 51, 102);">{b} - {c} = {=b-c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="100" height="40" role="presentation"><br><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}(<span class="" style="color: rgb(51, 102, 255);">{=b-c}</span><span class="" style="color: rgb(51, 102, 255);">&nbsp;+ {d}</span>) + {f}<sup>2</sup>&nbsp;- {squareRoot} - \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>
                <p><span>Finish simplifying inside the parentheses.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(51, 102, 255);">{=b-c} + {d} = {=b-c+d}</span></span></p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>{a}(<span>{=b-c+d}</span>) + <span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2</span></sup>&nbsp;- {squareRoot} - \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Next Exponents from left to right<br><span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2 </span></sup><span class="" style="color: rgb(51, 255, 102);">= ({f})({f}) = {=f*f}</span><br></td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}({=b-c+d}) +&nbsp;{=f*f}&nbsp;- <span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> - \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Square roots are exponents.<br><span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> = {base}<br>because {base}<sup>{exponent}</sup>&nbsp;={factors} = {=pow(base,exponent)}</td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d})</span> +&nbsp;{=f*f}&nbsp;- {base} - \(\frac{{g}}{{h}}\)<br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.<br><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d}) = {=a*(b-c+d)}</span><br></td>
            <td style="text-align: center;"><br><br><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="100" height="40" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span>{=a*(b-c+d)}</span>&nbsp;+&nbsp;{=f*f}&nbsp;- {base} - <span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\)</span><br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.&nbsp;<br>Division can be show with a fraction bar.<br><span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\) = {=g/h}</span><br>
            </td>
            <td style="text-align: center;"><br><br><br></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f}</span>&nbsp;- {base} -&nbsp;<span>{=g/h}</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right.<br><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f} =&nbsp;</span><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d) + (f*f)}</span><br></td>
            <td><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)}</span><span class="" style="color: rgb(51, 204, 255);">&nbsp;- {base}</span> -&nbsp;<span>{=g/h}</span>

            </td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)} - {base} = {=(a*(b-c+d))+(f*f) -base}</span></td>
            <td><br></td>
        </tr>

        <tr>
            <td><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} - {=g/h}&nbsp;</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} - {=g/h} = {=(a*(b-c+d))+(f*f)-base - g/h}</span><br></td>
            <td><br></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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MVM8/vX3yp8LWXLDyLRUwc4/n0QZ8Kby9YmI0sj+Z67jNnuXOl5olr0P62VhDHOn76mdI5pY5Td/GO8VuPdA42fR73k0aJRxxfjTqGOiaVosdIx86bK1XHrdLfPz0Wlc6rmCr2O5ZSze+zTB+DYmj/+ufLmwOxN2uNRbAhbu9gW2axNtVi7bu6UjegOdzSMDjc09QW5jYPC0ss1lYMHvHBWnTy6wmVnOTy6KRfKtZEsWCr5sSeR/sqFlN581SyzhSN9eJQX+suXpx4wfb6zTOzzypDQZXOW0wFRzXHIaLHqlxcVXuMRbkA0j4riWwPHUdvzry/K/GcUQ8dB28exN6sNVZtg01XCRDrzZXm+u0QbLqd+m9/c7bFWlPhyppuq/7EYu3OwnPhhoUFLcMLsab9x7Wkt2Z18tTJThGg70Xf1K0f5wqLrkzkfzbPPBqfP0HrY50AtT/9vz7XftI5nrKTsHf1SNv8xk6ycZ362Duhal7Nkc6bN09+jRHtX6GTX2uKt3apMMkfyzw6ocfv5dU23lxpsHnHJT6Gsljkah/e/Hm1hhT93DoOCqe41mK/H8WORzRdWzzGcV6pz/M/o34mb66oF2tah9YY59TaNa/3GOr73rxS26Vof+nvYLoGby7E3qw1Vo2DrcUmRqwzV5rrz6tdsL1poaaratP6NYVL9Jy1/oPC9QNawi0NQ8Kdja3hoaahhVuhS5ot1mzfq3JrkTpp6YT22rXf7/R1T52MUsptVwydrJ8786wu45860MIq+Vp6Aiy2bVTfS2NAkeWNjRZDx8f7GbVOL4Ze+qqFVjI274bksS9EjTOumGmw5dFx8o6f97hpbDour+ZJY1DH0Js/qp8tjSDt2xur45RH+yo1t+bRmFLH9827Osew1qI1eWOl9pcGvvbhjZXp76H2542T+h3U3OWOM2Jv1BqrtsG2Sq92Q6wzV5jdDbZ333yzcCXtxV/OL7yoYMaU08LUfo3hIvMyi7WrBwwKPxzYEn7aMDjcbbE2d9DQML95WFimq2vJOrpreoLTlQpvXNRDJ8V/P/AId3xqGjiVbvsrO2GmlNrO4/1NmwrzeOOl5ksD5a1H5rpjo12DbZ07rpia3+PNu+5xx0e97bxx0XS8wsMbl/qbm3+abbENHUNvXDp/ueNWTu+xWPfV/+2OTdXvVJ5N117vjkvxxiDuDFpjEWyIpYLtdYuxf+7bEM7t1xAutAi71CLsu+YV/QcVvDLnVRZnCrTrBjSH75s3WqjdaqF2e+OQcF9TW5hjsbZAz1tr3hZrK3Nr6InpCblccKTopFrpiVSmgVjsZOqZbqu1e+NkikKjkjBUsOYpdzy2R7CV+rmi+llStBZvrEwjppJjEU239aK31sGW/l6W+w+JvOm2+r3xxqV4YxB3Bq2xahxszTYxYp25wiwVbOdasF3QtzFc1q8pXGthdr3F2A8KtoQfZv7IvNGcoatpAweHWQ1DwuyG1vDzxrYwt2lomD9oWFg8yELN9rUyt+9a6AaHMy6aUrgS5IwrZv6qiT72xhTzNzd1PhEXosAZJ1PWfcWi0hmXqoDMU+54VHv8UtPQKVz5csZ5vv/qpmyrbRSCzRmnnz1PNfuQaSh7+0kfG63t3w+wKEzGVWp6u7LSx0+mV2OLPSZpiOpn8MYh1rvWWLUNtpXNw+1khFhfLjdfPu/C7F/5nXn9hRfC+RZsl/RrDNMt1m6yILtNV80syO7Qc9Iy71Kg6S8XNLaG+80HLNTmNLWFxwqxNtRibVhY2jzMgk3R5q+ju76SrF0nN29cNMUbU8x0X/9pJ3V9rVIVh3lKrTXFG+Op/aR446Lp+HLHL/W3SbDpc2+cp/aVR8fHG5fuQwGWP67lTIPNW+PaAw7vcgtTj++LFlrp2EpM8dZVyhRvH+lxEdUcf8R60RqLYEMsF2x6PtqV/ZvCTyzWFGWKMYXY49Ji7InMX5qKsyctzhaZS8xl2fy1ijSdPNMTWzURJFO8McX8j+QqTE8h2DoHW7Ft0+DqKcX2k/4sEa1Tj723jef/O/ML2Za1w9uPF5lCX9MtWK3D2w6x3rTGqm2wxasHiPWkoqpcsF1lwXazBdt9ja2FK2eKMrkwU4EW1dW0Jc26orZt7hhs1brGTkY6SW59+pkut35K8Z6dXL35oinemGIWO6F3l1JrTfHGeK53HktvXDQdX+74pabHRJ974zy1rzzFtk3H9ZRSa9ySPAcwj0JI33/WQsjbNuo9Bj3F24/Uf8SU+udDx07/HHnbItaL1lg1DjY7USHWm8vMl8+dmv3rvTMKtml9G8I1/ZrCTAu2hyzYnrBg0zbLc3PU2jfuutu9clAJheBw5oymeGOK+duHaxds+vk2XTPd3Y9M8cZ4rnceS29cNB1f7vilpsdEn3vjPLsEW5Ftaxlsiptnz/i8u5+ojkm5ff5u5aqwZv/Dim5fS8odU61DY0r9M6Ofu9TvG2Jv1hqrtsGmExhivbnUfKlEsF1kwXa1BdtPLdgezIJN28Roq7Xv2ImwJ+hE680bTfHGFDONk3L76okp3hhPLxa8cVEv2LxxxUyPiT73xnmmUVRs20rH1VodG/0+FguhGH/edinpmO3hags3/ceOnntXjB117BBrqTUWwYbYm4JNJ5sUnRR1ktFJUCekdJtqgyPFG1PMdH06MXrjamGKN8az2lio9vil6rHJU00QVBpi7z79TDZiG7ot6Y3bXur37j9uutW99ej9DrzwlW9k3/0Q73d3e6o1FPuPn1evme5ug9hbtcaqcbA12cSIdeZS86XvVBBsAyzYGizYGi3YbJtluTlq5R/e7HxCfGfFqm0nOmdsdH2y9kJwOOOiKd6YYqb7Et64WpjijfGsdo3VHr9UN9iccZ5usDnj0n1Uu8Zamq5FFAIoGZei45yO2RG+cPY3ulxxK0SmMxaxt2qNVdtgW9Y01E5iiPXlErN8sDWGWwc0hwcahoTHG1sL2yzNzVELnz/769leP0Sx5o3N+7ITHN64aIo3pphaT4rW7Y3tqSneGM/0eAhvXLTa45e6OQkYfe6N80yDrdi2CqI8ukXpjdtRplf8vHWnkfTGnXd3GbOj9P7Z8sYh9latsWocbI02MWKducQsGWx9LNj6WrD1t2AbaMHWYMFm2yzNzVEL3dBwxqW6weGMi6Z4Y0qZnoh1FdAb11NTvDGe1R7Hao9fqhtszjhPN9iccasndw3lX8+41R27I6zkZ94y/8nsu9vQ1eN0zI40xRuD2Fu1xqptsOkEhlhvLjbXlQi2Cy3YrrJgu8WC7RcWbI9ZsGmbGG210guNDjtRe2Oj+n4aUIoAb2w0xRtTSoVCitbujS2m1v30aZ9zvxdN8cZ4esfRGxftznHP68WLN87TCzZvnFQY59FVtmrWKXXMq93GM42x1++8u8sY7SulmmMT1dUx7+vVqJ85j46dNw6xt2qNVetga7OJEevLxea671yQ/au8M9uCbWAWbIMs2AZbsA0pbLMkN0etTNFJ2hsnX7Y1p895E9uCzd9GpnhjypnuVyfAjVdf547Nq5O4TvYav73WqeOS4o2Ldkw+NBv1IZsfntNl3LbA7Pw1qbF5vG2L2TXYim/rBZBifVvQ+NtEdUxi8BXbhx5TrUdjve9HtT89fnmKrSGNTFHJ8dFjogiMv2femF/PuKWwDs2n8d6YaLqOd596xh2H2Fu1xqptsOkEhlhvLjJfLBFsUy3YrsyC7ecWbI9asGmbGG211DvB6SSqk9dLtkapj9MTfR59z5s7muKNKafW4aETrE6gire4Xn2sr3lXAr25oyneGE9vbd64vOnahNandb9lgRm/325hkG6rMXn0eTqmmOnjWG7bdF+RuNZ4zOVrFjRaexrXxfaRR9to2/zjqPmK/X5680kdrzTuhL6m+TVnfs1am2IqxZs7PRbaLv/PSZwv/fmFvufNidhbtcaqcbA12MSIdeYi88V/LhJsz78QLtxjYLiqjwVbPwu2ARZsAy3YbJvFuTlqZft+/gmuFIqJfHAUTqDO3NEUb0wl6mRb7Vrz6ITtzRtN8cZ4vuQ8lt64vAqTStDc6babH0qCzT5PxxSzS7BVsK2OW0/Qz+rN2x30e6ffWW++6HNf/robTZWifXjzpse9UvR7682H2Ju1xiLYEHtTsMmnTvtcpwArhU7eOmHmT/w7KtikTsZpdJRDJ+9KTpop3hjP7gSb9K4epXjb7ehgk4quaiNI+/KCM1ptgOuKVrlYi2pcJcc3j9ai41FsH+nvfTk0X7FYReztWmP1KNg0WBtpY00yZbGejI1YZy4y15z238PbTz2d/at9G1s2vhqW/Pgn4dI+A8N1fRvDTD2H7YNg27adN1+t3GAnl7ftJJeemHWSUqg9ZWuOY/NXXbRNfp7U/Hz62BtTrb/68tcKJ1etLT3pax/6ur6vcd72nt1d56r9Dum0rfbtjfNU0ChE0n3ra/qet41CJ48+98Z5/uaO2dlW24JCj7k3rpgar8feCxdFv9atfeR/V0qpY6f163conVPr09fS371q1HZaT3qMRX7+ao5D/ncvnTMeg2oeE8TeqDVWt4Otj9k12AbaxIh15iJzoTnHYuze/i2FK2nX9mkIl5vT9hgYrrb/v8GCbVa/5vCQjXlsgAVbbntERMTtqRora61uB9twMwbbyTqJIdabirUnzUctxB60ILujf3O4qe+g8OO+TRZqTWGGeZtF3D0Wc3NtzBOmtvHmQkRErLXWWDUJtr3Mw8yT5g8Y8rtFul2EWGcuNH+pV4BasD0woCXcbdF2p3m7hdps+//7zUfs60/Y9xdk4715EBERa6011slZa6m51F5NplqsomDT4GHmnuah5okP9Wt+aaGuPiDWofYfHIUgm9d/cHi4f0t40HzAfMicY197zNSYBbltEBERt6dqK2usk7LWqijY5J+Yu5l7mI3mUHOCebB5/Iw+jQ94O0OsF580FWRScRaNX9P3ve0QERG3h3f2HbTcGusE85CsuXSxTA2mFl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      <text>Your answer is correct.</text>
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    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={-3,-2,-1,2,3,4};
b={-10:-1,2:10};
c={-10:-1,2:10};
d={-10:-1,2:10};
f={2:12:1};
g={-5:-1,1:5};
h={-5:-1,1:5};
pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};
</text>
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<varsglobal><text><![CDATA[g=g*h;
base=pair[0];
exponent=pair[1];
squareRoot=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}
ans=a*(b-c+d) +pow(f,2) - base - g / h;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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  </question>

<!-- question: 0  -->
  <question type="category">
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      <text>$course$/top/Default for MSII/Test #8/L62- Exponents and Square Root/L62- Expressions with Exponents</text>
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<!-- question: 361126  -->
  <question type="formulas">
    <name>
      <text>L62 - (a+b x d)2+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b} x {d})<sup>2&nbsp;</sup>+ {c}</h3>
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</script>]]></text>
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    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td width="25%">
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 51, 51);">{a} + </span>{b} x {d}</span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; Multiplication comes first.<br>
                <p><span>Multiply&nbsp;<span class="" style="color: rgb(255, 51, 102);">{b} x {d}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{a} + </span><span class="" style="color: rgb(51, 102, 255);">{=b*d}</span></span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>Now simplify the addition in the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(51, 102, 255);">{a} + {=d*b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b*d})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b*d}</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style=" color: rgb(51, 255, 102);">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};
d={1:5:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b*d,2)+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 361128  -->
  <question type="formulas">
    <name>
      <text>L62 - (a+b)2+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b})<sup>2&nbsp;</sup>+ {c}</h3>
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b}</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 255, 102);">{=pow(a+b,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=pow(a+b,2)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="font-size: 1.64062rem; color: rgb(51, 255, 102);">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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xPO+2filBexvr1n27sttubjeeYELvCgvxNFuTnG5c2HnnkiSJVGWeddbOlRSwh7hZa+cuNa0r1dZdrGtdcUxVsvzIbLmxy992vMTvmGBdb2tXN9PlyOmFdsHk9F1g9V1kd+GeRpaOe1VkRfPXVH7O011q62YVN4Z+wK/5PGauMKwvy/zRdlWsmWZ+4Y9H79uabv1mMgDzWr/+8jYurjbNsXCyxPCuezJsvVxTFnZGmsbor2HbffcgCjzg5rml88IP5n6I6/PBLG7vu+hbj20y0zTBhMte42PKsaNx554NFqjLuvPP7RfprLO2gcYmlX92sJ1//VLnGRMkXitod9933S7PhvCZ32+1Ks+Em4yJLOxU7yFcXbF7POVbP5VbHLONCS0c9qxrf/e5vilQtnHnmeyztpcZrLe0849IivduVPjxx332P2nfLjKRZYVxlbNeG1ZOqT9wRSd8ua3tSFbjzzh82jjhigY2J2cYFlme5caVxWx4f2AV9jrWoMb31WO0PxpD6ZEehaazuCrbddhuyBUmcHNeURELgnnt+2nj6009v7LLLucZLTJRcZ1xo6ZcZVzfOOmukSFnGww//ztKfY7zc0s8q8qxq1pOvf6pc07jqqrpg22WX8wpeaTbcZFxkaVc30+fLGY/kqws2r6PaXupZZT66w/zRWjQ/97l7Ld3FRvw50zjP0i0p0rtdVey66xzjbON8O77UuPLJtGXSJxOvT9wRSd+uaMyf/5ViJLTHww//e2P9+q/Y2GCOMHYZY8zXbXOMPP64vyeSv2ed9XH7bnnBiDEa19PLNRZvWzv7H//4/fYdY4g+WWHckrFfnA6axuquYNt11yELNuJkeOaZnyqmWhnr1n3GBNsZxgtswb/CeKOlX2JcYVxjXFoSBynmzfuo5bvE8lxrnFvkWW3M2zA1rmlceWVdsD396ec1iWDbZRcXbG4DtufKGY/kqws2r8cF2y67uGDzelY1ucsuC4w3Gq+ydBcaLzbim5lGfINPw66cIJxhvMZIGQsszbIn05bt8zonVl+aX9yxuNK4rPG1r20uRtLYePjhx23Ob7AxMsfIGI65zjjeVsZLeX5ceeWnmmN6l13m2zHsDVtzeTtlzK2UuXQ7Ojvzw5VXlm9HYU0g3nqsYRwRrxRvtmeaxuquYHv609fYoiROhp/7XP2nqMBhh13eeOpTz2w87WkXGWdY2jnGZcaVxtXG5Y2PfSz/g/AbNtxned5mvMp4k6VdWuTL2zA1rm5ccUVZsG3a9Eur99yCVxQ2LDSuaqbPlzMeybe6qKEFr+OtxsuNN1qaBUbqCS42zrVj1xuvNl5jnGGcZd9jEz71svPlX2a8xPgOO04fUF6uHXyeaH1pfnHHImNhhXG+ibb8HM8B4faBD3yncfjhlLHIGHM3N+amkz5mU1xxxYiN6+uM19uxecblxqnEmZgXtDUY3+XS76js3A/V2Mv48bhPv8y2NMScGD/lvOL2QdNY3RVsT33qGhMX4sS5+slLDCk2bvxJ4ylPOct4tvFSS/dO4zzjCuMqI3lXNE466UNFjjIef/z/Ng49dEaSd6FxmXG1sWrDVLm6cfnldcH2lKec2+RTn3qF8SYjNmD7ZG0gX11QeT1vtWMI3BuNC4zUE3UtNy424j/smG2cYyQdPllp9LLz5V+QtGOWsV07ooxO60vzijse6WPGCWNhrp2Y5U+u2uHxx//LTsjutRM3xsv8ohzGVjpec/VuKXqdKS6//Hb77irjDCPjfKkR+3L5x+aGDa0nrNeu/aZ9t8RIm2PO4Mt83h2JDz/st8fQ/6efPmLf4Qf8St/n4s5Ki7ePNvOAD3zgmxavBux7+iTiYbpuiNsbTWN1V7D19FCoODGubgwO/ksxzcoYHLzdjp9lPNd4pfEm40LjKuNqI/n5//LG5s3/VuQqY2jos3b8QuMM4zzjEiN5I38njPTUtdK4ouDy5P8rGgMDny9qdSDY3HZ4hTFn/8TrgVV4HW81Xm680bjASDlRF/mWGRcZ8QOcb1xspHzqI53XW0Wr/MuM7zTONS41UiZlk28i9ZGu2v6UOV+Qr8q07siTKy9YLZO/af44Fsej3vh/mjZXfreYsyXX9qpN49mVlht5I38wrS+to5PycyQPZdH3s21ej9pC/J/FyOoM7JgMDX3N8g8aGVOMvbB7MjZNlu6/FAMD/2DfXWKMuUeMwWe5/GNz06bWfVgjI/9q3zHPIHGD+RT9kM+/Y7AsiAcGPm3f4QPiB77N+YDv8M8c40wj8fZi41XG643EH8Yg4yXNJ24/lGDbBri6dFYZIKD39PQb32IMwcWkrQouX2CGh79b5Cxj48af2vHzjO0E33hcbQvFd6yc35hNrV1A7pHYsOFnFkxGLQ02LbX/31kcdUxMsK22/F+wMn/+5Nkl4Axz48Zfmw3ftDQseC6Sqmgv2FY3+vs/VbJ9dPTH9j1lQV8E0oViIujvH0nK8YW9k/rG9r+LeHyxefNvi1Ja4EyaMgcHv2Jp8T1lEozHXsDpxwD29fbeat+7P3t73908jh9S26mfuvr6PlikHb+eqbK3971Pjrl0LADGA+0fGbmv8H0qmsOmvF3pPKMMz+v5R0but7b+rjjq7aaOGNutdk+2zeSlDMblbGvjQiv/nqK2zrFp02+sL95lZbAwM5ewLfojV2+3Sfurgu3v7bu3GweMNxjxWTcE2732HSdH1xlpL/MHH26Zcbdt0MdvioGBj9l3+AHfItrwQbW/+Rzja5YRn7FmINbwHSJ/OseJ2H12XbD5YBM7Z2/ve4ppWQb3n7lgO8fI2SsTkMlIgE4XJv6/0oL4B4qcdfT1MckvNTLpOdOq7hjkuKopGqoLZg4bN/7C2sEOW/nBCRds2A8RUgQS2hCBw+vq77+jFKjbgV3E/n7O5mcX37TgdSDYYtGgzdSzsikEU2za9LB9jy0ISNItLY5MHCMjP7D8CER2PnwBre801uvzPqj7HKHSic8D7LwMDNxheakf37JYhrgoj5ORkQeKXA7Px47PXU0hNB58AZ1tZAzF4lmtZ/JkLiCcOrElgG/7+t5r+WMXJnxbHd+ramOMPuntXdkcV+3gY4l+o83h28m01+epi0sWT/x4rdnOCVu5X8YDJ3P9/X9n+avjqTv9MDa9HSkGBj5k311kZPcZgUD78FMu/9hML+uNjHzPviNuMKeJf9EH2DAdbd0azPn3H+07/HC1kT4PQVzNx3fMS/xEPCBtOi+6N1fFrUEJtq3OoaFvF9OyjMHBD9vxvzZeYGR3ClGQnmGmZBIuMeH0qyJ3GcPDX7bj7NJdY2ShaCcYWkx3YzoBryUYHv5W8cnhgg0R1V6wIdbSHZ3xwGI1NFR/TYLX006wVQXUb+x7fPEOI0Ftodk/9ruy2mFw8FOWn91LFhS/XDV+fSxoLNxp8FxV2gGaKIaGvmpl4N+qsIg6coLtI1bnT4pPnWF0lBMJFmXaGjuGaT2TI2It3eGaCBB4/f2IBsZ2nNRUBUxdsPX2zrU6/0/xKQ+feyyUMaamIhjIg134jEUUH+LLq82Wm6x/vtMc353ARdv7LW9cnmdMUXZdqPp3HGNM8DfS5doQbYs81fR+LEVLsMVJIW0LUUGdtJe/UX9aVsryfVjsQPrOHZf2mD+pQM2VVbW5yrBhLDuiDNJgdzCXr+q7KtPy0vpz5UWZfC5fQSjvYBJn8EGsBWl+iG8YC8wDxkV6EhdtHMvOsGsybU/LSRm28f8oK2WkaVeu6JRg2+pMA1SAhwV6es4wnmkkELK1zbY2k4fBnStruS3a+beqb978iB3nsiiiiYVn7DPg6o5UAFE2OvrD5sLCrgCfx8KmTb+w8rikmxdsXPrKiTUWow0bftSsZ3T0XrO/7qMqvB7YiWD7lX3P4tIKgH19w5bus8Y7jPV32w0M/K3xfcb3G//O+CFjeu/OtUa/TFW/NJzWx4IWiw4Bysnlzxw2b36s6YORkY1Nbtz4UNtFfWjoS1YW7YnLZfQxPqBf64ItV87GjT+zdPc062rn94EB7q1stbcVcOtjqROOJdY2bfr1k21nPODLHFzADFt5CCAWKhY07IpFoC7Y8G2KaDtjPMZ2q3/xa5Qb/VZvy/iMvNjGGGA+4EfKv8p8cWOzne36OAVp+vq4VBKirSxU05MhRK1f1mbxTtOV25GeNIyO/sS+Iy2MseRMkQo2Thw2bXqkOOIgxvktDcQd6o845vVP5ISNEysfc/SD29Xf/8niaNjsbRwa+lbpRAw7+vrYmUxt4OrEP9rJ5r3N8ZHu7vL/sL239+ZavqrvUjKmo8wUcYuBX86Pvii3oRNs2PCQ5Sv7c+PG1gu72/u7bCdjZHT0p812psBvbAB429db2patubZTTiAdN319f9/8nN7aEbfTcFVovHLFlBJsW5UEihw2bNhkxxFrZxtZ6GOxKAe6MpfbxLqlKKGO/n4mHWeq3JCa7hRU7VplE6p+SW54+F/sGDtYiCLs8p2z4eGvWmDLLy4u2N7cTJcTbLkdJYRaby9n09RDXhd8iCReBtwOrbRclhlPsLHzd77xbUbqYqeD9CwE2HhNkbKFnp7TjVyipl9oOwKY/PiUOmP3bEFGsKX1xb2IrYWfwF4FYqKvjzTcm0e73N9xTyB+r8IXcPowRBt9TCCknpUmBO4vUtaxceNm8zv5sJO2eT1DQ6NFihZI621GtOE7Ai7jsjqWOuGq0kIT8HGAr2hzuf18v2FDvS0ITN/tDNEW88XrqS6eAfw2MICYYTeb9nvbvX76jN2NOGliEZzqwuL94bbhO8rEXsYePo0dt42Fhe3hJwPMrbjdgT6PcV8+8fJL4LSBuqiT+knbsi31EcLL00PmbWthTYFg6+9/V00AV8GlZy5B+5hhrnl5E4X3L3ON9rKj3ZpvbvNsGx/59975ZX38PNdsWW/pflYcGRvceuC3Y+ALYkWcEJT9R99ydaITETo6+oClp7x51obPFt92Br/NIr0VY4l9l+5O8sCGt9P7mrng8QY7EZQbM/MuB4Tr4OAXLB872NF2yqPtXl4aY2PcjIzkf7knhT9IE+Wm8crLFVN2XbCFo8XxyYMC9YUaDAxwTw7CgAUqdowITkwSBjSBokqOcVn0l0UpZYyOcj8ICzFPDTFB0p2Rll2Dg18rcrQwNPR5O0ZeFk4Ws1SoXGaB7H3ZYO2CLQQO7YiHAVZYwHh3kaoFFmlfMKMeFtBWPSxi7DDl0BK4pCWg4y/3TV6wRflc7kqDMAHuhiJlC77jySVq2hL36+BLFnJEMMGxvoCAfH2+8OOHanBnV8l9TP9XhSF+ZIG+zPqlvhPqPiQNCz9tiYVlRVvB5pfM8XlaFztL1Hep5avfHO+X2LEDX8diXh5LnbDaNwCh4r6i/YwH6kI0Rfvhpc22VuFjlcuYYVcImBXm1/yOYX8/L6VM209dsSOKAETUxxzEn5Q38bbm6bb5/KVs6mB++o5bfz+7j2PvMPsOF20OG4kRy2u+5RK4n1hQdgjtdIEsX5L0S/mMb8j4dmGAvSmGhzc0RW8n4BJ0by9jn/Lon8U2p39tdT3SZLrDxQkaMcT5S+OvkvGNTbR3rrWrdVKBkNmw4cfFpzpGRr5redjJXNLc6amCNjvrP9pPG3lYJOptCYzWWJjorSTDw+yEXW8nWu+1OvHBw02m4ApJ1Q/Dw3dbvrgVwwVPWbBxby3jlnlAX7cE+mRvPxgaIk5Eefgh1iLmcSqa6YPOb7UYGPiolUG51ROJGJeiU4JtK3JldicLbNr0c2NMToIZAYSJ7EFtLHImmAPBzxelVNC0JlyQ4JnCz+ARQkEWNAImwYCzegLGtRYEuB+oLNpoRzvBNjz8gyKVw4NhurPGgs2iicChjuA1FgweLHK14IIK+8gT7aNt7QRbiCFEFwIKu2LRnF+kbMFtoi20n0CJIOIsn7wEmljMlpWCF8jX54JtbD/QHvxAn4UfaBsLBr6fWVucyO8iJ+57RIj6Ap4TbEND/2zH2Dnk9THYiBglLwti9O2iInUL7Hi2nl4mgE9OyOTHG20PhjCkHtoc7ce2GTauy5fl/alo8uCv9MQkL9i8/W8yxutzEGv0EcKGuvBhulMRwrSbCwplYSP9xBjCZnxKvfm5lcLbjMhm3DAmYxxWBVt68zplh+Bo2VEWbJw4MG8h/g7B2n5XDLHNCRxjtrd3lvn3C80xmcLvTcPW2CHCry5UiXWBkRHEDHMOMjbp17hEnRdsqeDDZ97my0wQMdf+xf7Szivs+48VqfwS3dDQBrMXGxj7zDc/QazGGred+R+XofGHC4yqv7GFByf6+jjOuLrY0vxvK7N1ouECMuY24xWfvLM46hgYuM2+wwfEIOY2ZdEnjNPIVxVsnKATC/FTiGOfB1WxhogeHPxnay91U/bbm3bmTo4HBri3mhNUxhnj1OdDNeYF6PuhoS82fYlP+/vfWyvX53y0hfFQHZeiU4Jtq3Gi9yx0A4ODnGET2FmMEA1MNiZxy6404IGhoTvtewIFARPxQLBkYhEECHAELSbZjTZpW0EQIDp9IawLtupC7WfOCBTSImwImgQG8lBHkIlfDmjAAxr5U0HqAaozwRZnjL5TWUVLSIb/IgiSj6AduxXsbHQu2KoiouWH8Dd+QxyGH2gXIoz/z7FxVH9p8sAA94awsOG/6Gd/dUUKX+jxG2I3xAqLB/7Dz9RB385pBvUULthYPGhPBG9fuNLxNDbLl9ZAa7xhDwt0XOKkDtoe7ceu2bYIlx90Ae47/BbjwPul6mtvf+yckifajxBgEYy66Oe0j7sp1qoM8ZbuuN1ki/7NNeGTwv0Vt09g75LaOPTLvgjy8A1jkHqi3qpgYyGlDyACK8RVXbBhW3//WjsW45YTG8/L5dLUdv7f24uPw9et/qwLNuJHTrAxB+uCLcCuZG8vYxO/ME6xifwudvr61jdPbv0SKT4jLceY3/iI/+PPS5p+CPhl9zhpo/50fJVFtQtXysIG5n7YcFHTJ5Tlt5rQpvAF/XJdUYLDBRt+IC7kBBtzfF6p71xYRryOy+Xc51x+yI2dMK+fNoWv+D92X2zpq7GTMUH6WEN83g8MfK5I0QI7g319HKftUa63P/Up6OtjHKY74y4E6/NjZ2bXBZtPenF8ciPmdMPvjWPixOWT8o5BTkT6fTwsaky6EAEs5BHsg9xs/+kil8MFG4svYocAE8F5eU0YDg5+3L6nHgIzwYIFgoDA5E3rod52O2AENIJsnP2OJaBCGBJ4yzsx5KnC01fLxx7qiHzOzuur1+OLKgtU+JvAyGJG+vABdfKXvptb21X1hY5gHf3sYqMq2FoLIiSQpgsoeaIO7o8p30g+MvIt+55+ze3Y1sd7nXUhDdxPtB/7GTP4OrUn2o9diy3Q/22RswUeDGmNIYQeZ+xLrQ1lwebpqAumi3AItLS+tJ9z7ekmqSP6GDto/yzz+fcLy+vo719naejDEFb1h198bJEmhB1jKua/t60u2OgHyNhg3Pp8TOFijfoZRyz6+J5xgaAg3zVme/k9kYODn7Dv04Wf+YToaF0OHBn5tn0X8w67Y+eXMcEJE3m4Z7Qs2LDHX2VETGAeIcLCHvJzAkQ/0x7KYfzyPeUzBrA50s2s+b0ljklDGUus/R8vjjp8h4sxBfEfbaX8KJu/1BWM2yoYr+XXFg0M8DANfqBeyqGPow34jrYuLPWd31ZA25lD9DVjYllzNzFA3OjtxX7sCzFFu1IfXG3llk+u+/t5fyPlYgP1c3JQ7gMXzIhFYgR2MCbIQ9nXNHf0Uvh4oJ+okzKJ89M137YXSrBtJa6oCZbpAE+f9vYyETlDI0Aw0VnMfFJUF1AuN7mAqi5oBPrIF4sZ7x8r3zjrgo1gS7AJweYLexV9fUxQ6kFQVhfqqMPr4bsqvJ5uCbbcLx3EwtFOsLX6trP6Fljg+0SRogXvHxa+nL+jrtTvBOqqmEKIUReLFLZ6/rxgi/6JtAR26qJtUc+yTB0Itpw/Ul+Mxfplcd+9wJbYyQzBxRig36PtLbvwYxUuxFiEUsFavikbeDrawKJCO2K3Im1/lbm2bElSp/dzTpwGfBeGBZ02s/DPt+/Kux6+K8q4YtHvVLAxHyFix8ctvkkxOMgTj/gx5i++pO/wPbbMNtv/pkjtGB3lHivSMsZDfC0ujTOelvU0tCuER9hAvKCf6i/s9l93YQxhD+OAvLErTn7qIg4RX+hvvwzpafhLuhBC7OCVT0R9vISApI2LzNbyT475ZVDGMvUzlpnXpGU8M8f4y2fqIxbzf77HroVFKY7WbnZ6EkIb8EHMjepDBwg2/Ma8RlgN1kTl8PDX7XvaQXsYF/Qbggl/hJ9usv4trwvDw7ywu9z+auz3eM7ONeMC27Ej2knZ5fuEXZwTsyiT+vE9435rzLltlRJsW4ErbALUb+yfLgwNfcZsIIgQQAhKIVTq2+UuNJjMBL8QeeQhQDCZyu3KCxXyE7hago1HvavwNARYAkEEpVg4y/VQdxWevyogsHFLCrZcQOlcsFXTgby/8UHV38Gltvg9WOR2uFBGaLNQhDBfbEExJ9jiEhbjgQWjembr/88LNuyMxR9/TEywVe1pjRcYArKdn70Mxkj11yBagjX6ygVrXbDFzgULSgiSdBxU69saDFuYC+WFPIULNtrSmmfTJdi8XOqGlB2LPuKD9NQzWDpJ9b5m7MXJGWOPXdBUsCE6sJf6QxwwHlyo+Xir3zPaijmQMcAccBHrtiBygtiHnSGimG/UEbbjx6pgo1ziFLazO1fe3eLeOT9OOuYgcz7GcohN/rog9DpdqPmx8i0ZrSeYKQtRSZ7ou4gN5R3knGAbHi7vFPb3v9u+p9zYuYt+S/2EnXOLHA6e0PZ85KFsTg4+Uxx1+PzjxJO+ow+wm/ETts8tjQcX5yHMJ7NjvzOw64ItgovYnsttwOffuTU4yA2yf2V8o5EbwTlD4TIhQmZi5Ifjc+B7DyStwB6BL7+AIlJCQMQWeASKcrvaC7ZYgJmInLHW73fwNExwghKBg8md2+lgEo8l2KoCot1DAKQnQLAQEKgJTF72xMqPoNKyr7P66jsgoOXvCIa+kNXrCXKps3x274KN+ljs8KUHyfaCjXSIZNKxYKR1uT/ygo3+qo6LdnZWWX8Iov2ObM7Pwdzl2m/Y9/g6bPNFMi/YcoK10zZMJ/FB+1/k4B2BrXHjAmigcpnKhRVtTf3CHKP8ej/7uGXhjRMNH7dVO7xc/M3iHDtmnq7Vd/g/LRsxSF9jS8z3nOgIwYZgrM5Ttzsv2LCHtkY+7Albgu5TfMB70YaHv9c8+cEGpz/IVf0lDC8/FSwLmukCLaHLOEasxPyIeFav38n/3WcpXLDhh1y/BXO+Y2yHYOU1G+U40epbGDtbzLe03/jLSVHLB61xEfNmjtlYFbW0n/6N3UXGhItRLze3m5r6a7y4tzNSgm3a2dtbvjQQ8JflItZ43xcLYSyknKkx6CfG6s2iKfr6WJhJx0QOYVS/x8knJpMOMpHiLDEmc9q2bgi2ToQKn3d0wRb+dn/l6wkus0Wm/KSo/6wZ9aVCZEGtf12wYROXWjgDZlHjrDot3/2RBldQFmyxEziRADuWYGPsc/9LLPxuQ76cpbUdNn/ykzJijFNGO8FG+5ljiAYWq2r7txXS/m1ZsLFAx+44Y4FdlOg3WF6gW4KNPmrtqHdHsDH2ycO4jhOWEOKtfHBw8Ku18TMe3M+UH34s31PrbcNnjMHYMcKGdH6ELR6jWnPc/5+iO4Jtdu1BLz9OOyjbhVe538LO8i0R9XExy2ws/yyhjzP6gfGYrjPRzvKJVl2wTTSe7AyUYJt28vbtHPyBAHbWWASZCAx0JhEBhwE/UV5jIjD/VNnwMG/EZ0IRBDmr8jOfauAjf1lAdEew5RYef7EvgTCCkgRbp4KtKkRciFHf9ijYGCssJPgJwVZdoKusjyW/PDhRwUb7t23BVh1XKXxHfmsJtlRQhL/HFhQtwcbYiziEqOuWYCNfzNWcwFnR9krHeCg/Ve3tTdHyW8z3Tk48ghzfMoKtOv7dT/g2nSe58c+4qPYd7aN8TqxuMBurgg17OZ4K1jSO5ezFnrBXgq1OCbZpZ/UsJzA4yM/9xI+9MzE56ySIEaQYvBPlLAtIPy1KL2PzZt6SHZOZgOYTNbcg+KPxnQiIqQm2wUFenpheYtvxBVtv761FihZcRExMsFVfAOr3KVIfizPjaNsUbOxuVDFRwdbXV3+tSV8ftlBGp4JtrPZPhWG3j0P3T/Rlvj3tuaytwPD5zM484ybdyd4ago1ySTMRwUbZ3RRs9D35Ir7VBc7g4IYitYP7qYaHv2FlEYeZ45D2+DvJUtQF27zMJUOOx3zv5MQjyPEtI9iqO/E+1zoTbOkupPcd+Sh/LMFG+9N70tI4Np69E40nOwO7LthiQIo55m62B345lJd3EnQJqAQw7t9hYsZ1/4lyoQWlLxU11OHvTGJSxSUMDwJV1IVUTKR04YHLaguwBy6CMoGBiehn/tRTFQCjo9+377n/jgDOriLBmeARk7ZVT07oeB2xw0CQDsHHU2Tlnaz8Tg7BKhbWcsAE7cuv+6Gz+ghg9bet+y9SpDuN7fzt7O8vv/sOuGBBsMWlvhBs5XtYWoItvSSYXjqC7o+8YKO/CPaIneolj/G4LCu2fLzhq7LAb1cu9x2l8BdEp+9VCwGRE2w8JTpe+yfLZU0RQJ3+u5GUC2NMd+onZ85XgeHhuywNsSP85jfn1wUb7+djoQ2hEQs0ddT7OS88fNymKAvBarnBJU1/BPznzRjn+J6ysbn8xHNZsPmlt/I8dbur883HflWwle0p/7Zl+noL6qK9/KWMC638nGBjfMXYn1uy25925njqt6rd7cjxqiDuzL91AYQfiFfYyE+dVZ9kpRzEeLSDvq2WC8vx0C9fko82uiDjZ89SuL1xPK7MpON+PHsnGk92BkqwTSOXWWAtv8YgsGEDv/sW967F5AnBEoN2oiTvwlKQTOHCgIDCGRJnt0yoxaUzReD3Q+UWZiZfq308Ml6tq3VPEgtJKtjqTzb6QksgJEhyNk2Qow3lergHMHfPidez/Qk2fsQ5hb9UlDRj+ztY3bH1xSIEC2UQ4KmLhw62LcFGm6qC1X3ViZ99LNQFL8Kf9tOudMGeXsFWHQP8rmJvL8fwk/dHq1/dx7ly+J4TlHb3WfmrejjJoS/SnbB5NTHvr99AiKTjIhZot2Eygm1w8GP2HQt0jAViSdmPVVt80aefsT0uidJHOcEW7coJn8kJthT+zjRsp53RDoQvdl1t5Y8UKR0ep1OhM9fGXfln0lq/g+s7UO63dv2cfsf/2wm2XL8Fxxdsg4NfKY46/PUntCPGf73fsKe6G+nvzCRfjAtemp67h02CrbuUYJtGLmsbdP3pUBYZBmxnOwvjk7xLaoEk8PDDv7Xj6cLIBFlsorL8gkvg9wQxAQma2BYB0INLTqwBX3wJboipEGzerv7+jxapWvCn+wgE+ACbCEwEEK9nrIXL69lygs0XuxDUBE33l9fRygc7F2zYVn6BJHCRjL9JG/7GD2ldS7P3Q/Jj7S58WZjxIz73/NuiYONHqqvwS7rYxP13LOTxioFou+fN/XC37xpgV/jPd27IvzUFG0CM8xLWvr53WZrY1a6OobQcH0tVUZpiZIR3afGwEnMs2sHYp+yysPLXMYRgo8/S9i6rjadOBRvt8peppvXj81Z7qn3l6UOw0c+UXX4wgZ8w8n4kJuTmactHKcYXbOX5PTj4SfsOvzBHaQN1McepD6FzV5HS4elIHzte82ppWi/9HS+eR1tSlgXb8PBX7Tv8MDXB1tt7c3HU4SfJ9C2+Sh8WwYaWfWm5fkJJH9Mn+MBPECTYpoNdF2wx4MQqc5eugF8O/UtjeoYcgYkBngbziZB8PK5+e1FTHYOD/C5c7GixMC6wyThUE1/Y6Gd5MZkIyNjHu73KIiCFCxXEQ1VIMRHrL3wFHpxisfadAurh7LDdbiHwehBUcRmM4EM99bdwu10scHEGTNupJ/zNk4flnUZfvOgjbPP7C/v6uMTEguf1hM87r488/AZg+ceeAT+b1NfHJCU4Erzc37C395as31uXoPEFAZOxFIKlnWDDpgjYBNUI2Ok44n6TdoItdwk7zd+O7qve3jXZfmXB898fZIEKAUL5S8wvH8zeC+o2MdYYB9hFm5hL9FE7wTZe+yfH6hioYuPGn9tY/7al+6S1k5+doW76mPfzfbZ54pSbHyn83rW4lYLYweIYJzq0o/w6BhdWt9j3jI24J8zn18jIpiJVCz6eWETTcYud9RdXt8qOBZr5h995qWrZF/5CboQCY5X52ho/aZs9HaKA+uPkI8r1sQCr5bvNtJGY07ok3uqfsiDasOEB+w57EGKIIsYCIouXzd5eG58+xvB3CF98Un7PnPuDX38gDe1jHPo89DH8d83xyJWG6Pe0XSlcaFNfKqzIk8ad3O5kCKDw7yIra3ORwuFl499qv7kd1fve/CevKBd7IhbmXusRgi1OviPuR3zI3a9YtXci8WRnoATbtLE68AP+dCiCjeAVi1+coU5lsJIXzrfAl/9BeK87nVQEgfk2eeq7HoDLbfzEDLsEPNBQDWT83mT6I9X+4+/tBBuBvPyyxQBnfqOjP2zWMzp6v30u7zBQ78aN5TN236HsnmCrXrIF2IWQIGjFbx5yZu1tikWyvkCNXR9vsL+t5ssAPwuDH0ZGfmD8obX7l9m0LBB9fZRJPSw8+DvdCayL660v2OCC2u5EgDbRz97+e40/rNkR8EvB9H/sZMYCFONtegVbb+/6opYtA8Raby8LZvxwf12g0u7h4XuKHA586pcw3T/4vuqXQH7c5gVbgIW3rw+hcoPZN2SfN9XGq9dPmSzQsQvm87UqHBFT/usfl1h/fczaw8KOuKGffFxX59vYgi0/nv1EMezhB/dX1mwJ5AXbXEtfjpv4mku/fX2r7Tht5L7Cz1ibWrELO3zupDGkLFyB23e+2TVo/vuC8Yv2mTZFX3cm2HKxBmHuu4yMH798Ozj4Zfu+PC4Q0L29tIP2I6QjxuReLizB1n1KsE0b213WGBh4rx3nLDkd3NUzwsmSwb7QxEf+sqjf/8KZdioUPWi0e8K0HRAWvb3XNyd/wAUbQion2DzIDA1N7FcfCBr9/e9pBsIUrXsAuyPY+vqGa4EtB8SEt4uFkrbxuo52P9GVqw8/LLQ2/UMzwE8GCEl/LQq+jss1XNaJBdb9sG0JNkhaxvk8Gwf1J0Y7BWPOx3HcVpDu0DKXqKd8CQZsScGGL4aGvl7U1F24WGM+ETcYVyyOcfmXMUg/+OLY27vWxkf+hK0KTrg2bGidqPi4Ze6m47Yu2BgLnWLDhh9ZfvqIHS3sZhe4NR/YtR4P3s4QOfX55uW3E2yQWxHqJ4vMP56ArP52ZjUO+Eko9qeCjTp4gW59t3wsjI5y+wPzh5ML2oQfGDt3FynyoB6POcQ58vA7rOMJNsbF/HHLzgHf8IP1Hlsol7bHDj67wtVfOpBg6z4l2KaFuftZgN9Hlj4dyqITl7AY3PnyJkZ+IPv9RY11+KLF2aLfi9BatHgMvPwaiBz8LJLJxsJ9gU3CVLAR8GPXI+5hi4kLmZCDFkA2dCRWCPa9vZTxNquzKtioh8UrgvR4gi0WjRA2qWDDb4jJ8QPbwAD3H7KYEbh9QcsLtnb1hR/mWNsWlxbMTsBvMvoOBOXjZ8QHuyf4AF/Tl15PXrBhEwKHIDlRwYbPY9Fqf0/f2KT91HmTLQhcJsq/9iYHxszw8AbLS7tpP2QcMpYZJ/iYhdrbXxds1Rfndlew+UL2iQm1aTz4PWvsyLOzhmBmAY3+Dvu9z5ycDNw+rmhjJ7O398bSvGrN37EFG/OO+w45ARwLo6P3WlrKih0qTq4YO+k4XWTp2s8B+tzjJDs7xMrZ5uOqWGAcjC3YqK+T+e0niOXfcPV4TR0x9hlnfkmTnbkNG/K/MlMFcx2fux9oE8KGuIWtc01Al2/LSEF/+UkGeYjbc0pztL0Aws+I3E8029YJGL99ffiM8ug/+i7GnM97Cbbp4NQEG4nJRGYKMcGGc8UqueemOvnYFRka+pQd52wNoRHBi4HKhI3BOlX6wjE6+oAFu/KZIoLRL6MxAdMdGern+1l2fJ3l/aHZX17sCOb8CHDrPW2+aHIJI+D3R8RiysRlESUgYZOLKQ+miJWFVt7dVm5L8IHNmx+x+r9ndpCuVc/QUEsE+82zfA8jSLcuBfJahbTtbhc2sVinC1HYhN/wwXyr912W/sel9rMw0f7W+87SRRPh8ZEJ1hd+wOZ3WJ1cjvlOs46qkKWt3N/mvqfPWFBh2IGfWcwYRwTnGEdLzN5vFqU43P5UsKQLZ9DtSx9GwabyQxjpuA3/dUrSY6OPNxYhXqOAEKX9VTAe8KfbHm2HLA6IVfzLAoEvy+1PL0XRBn+1zXjtnyypl7Lwy0xr0z9Z/a25MREw3rh9oa8P/yAWiBmMdRZFxh39zbG4DyrtA2yYZ2MFwf7dyjj+z6ZNAwP/YGkQuhfZ/1uvHvKHX/Ar9SCCqcMFW4xvFnP34Vubc5S+YYwGEAWcaA0MfKhIR6wJsUbs4F4x+j78jv1cJv98U5Sk8Et3n7Dj5GXse7v7+z9cpPD6vB7aE2KB8ik3fNLyCz9KPzr6rzW/8MDD0NAXLA11XfzkcY75eGOuEWuwAZ/EPZaMIV5z8ZFmu+tx81fNeNrXxwLMuGP+UAcnXfgiBJvHxeHhb1kZrdtM3LbN1mZ+B5T2IdrId5N9/6siFXP78/YdfuBEGRsjHlJ2jMtrLd0Xm+WlfQaw2/uNscG8or0xVyiT+dIaD8S8gPcB6ehn5mOcqFN/jM3FHdo70XiyI3Pygm0PowRbR2TAQQY2CzWBjwDIAkvg5S+fCUCcMfoE6N5ApRwmKYGA4EWAZ2IgfiLwMxmr9ROA+D/fERQIDkxcJiFBHFIOn7GfAEkAo3zKYuL5IuAkOOeESgQnjrHwk5/Jjk3VeviOYwQ47CEYpPVwDP/6DcPejqAHUreNdpCWYEnbCA7YkPqcPAQ2jiHEqCvaT5+FXXxHObH44Gfy8beT+qp+IAgSsMhHevJSTzviE9Lge/L4IlYfR/zlM3YRQGkP/UYd6cIWC2dK8mIbdhOo8T/tIX8EZMpN65sIyUO9Md6og3LpU+rItRvG2MMWxkHsUmAnbelW+yfDqI8y6Q/Gts8hxC67mwhSTpqq4DtuJ2A3rfX7wrETH+IUu+lvxiZton9y/ue76jgOn/rJjzP1JWXzN8YWnxm3LPLhV+YTfcV8Iw0kP39jbFAm9UQdMHyezhfGPmWGvXwOe4kH2BH20nbKZbyHyMEmbKNfY77FfOA7fEOZOb+4oHa/kC/md4wvSP3BaBNjE9vScYPviZv4hnrxDXOFPNgdPojYAfEVtuLfiI9hG3bTPnxFOaQnP36gTOzFbvwUc570+IX5kB6P+RmM+Rxtpz2UX7UzGPXRZuYntqbt5i+fY42JGIEPcutatJFyxrK3Op53ZqKxpibYDjGGYHttvhLRB11MkAiaITT4S2BhoEfgJX23BirlMPAjqDFBmVAECernb0wS7EvrJ8gx0QgGHGfyhd1MRiYYwTeCIxOZdExQ6iHQkCcWlmr5Vfs4jh/Ih42UTV3Uw1+CALYS3Cif4JTWwzE+Yy/lUW6Qz7FwUjZpw+8EWAJt2JTahb30C+mog0UXW8IHtJ3yKDeCZuq3ydZH2/AneagDX+CHIPXzXYwf6sHv5KVsbMiVj10EScqmLeSNxSLyRZ40L8GVvLEQ0R7yR/DmGOWndU6EYV+MA+rBLuqh32McVNuPb+l/xlf4H1urtkyl/ZMh9cFYyLANG7GVerE9FSKcQHGpsMrYVSZdiB3ajM2MkZhT1f5O7Qi/+q5Ka34xroJ8xhcsnviGv/QzaSH9EeOW8qgz5ivpgqQlL2VRJuOT8vkbY5XysT3iXdpXOXspN+ylDPxHHdiEDdiEbZE++pT/812Mh078wngLWyH1xtzFjmgXaWPOp/ONv3zGrpjDMVdSf0fZUU6IGvKGbdgdsYD2pP6MsRvxLvom5g71Ym8cT+cnpGx8T9vpw5hrOTshx7AVP1XnGf6MdnOM9lAe9VN2jNGom/TkIw/tG8/etN92ZnZHsP2B8Y+Nr7EO+/dWp4gtMvAYzAxCBiODmIHJIGUCpIE3JkGunMmS8ig3ghMTJOrnL/bEJMFO0gfDbvJhJ/aSjwkJowzKZNEjHZOQ8kjP97nyU9uiHuzDDwSvtB6CM38JBJTF8Vw95MGGdGFJy+d7jpOOciDlhN9Tn4Vtqd9y7cemtF7KIhDxd7L1cTzalvZV+CL8wXeUTRrSpvVTVrVsmLOLdlEfPiJvmi8YdsWCQL5qu6OOXP7xGHmr44B6YgGItlfbj/34lfG1pdo/WVJnOh7oJ+rEdhbcEG9xAoQoC/KZ7zlOOhY08uF/2ouf0nGeqx+GDaSlnbQ9/ApTP3IM32Mn/od8X41P0U8xLyIt+WNOUmaM3ZgnfB99RVnt+iqdBzEOohzKrJZDWv4fc4Y86fGcf6r1YHvMt/AL/48xEr6I8mPORTuiTFj1D22nvCDl8h3l4NvUH9Vy0nET/oz82Mxx6iI/5VBetCVspI1RZpSfjsucnRHfqCvKwk/kqfqUsvgubKVd5KHcdJxG+qifY53YK5rGem2htdBcaK/9jGixjgQbiX/feJTxFcbTzPEP5isSfXAyaJlQDHoGMoOTwZpOuC01QGNCUQ/1Uy/1Y0cEDOwjXZovJhZ5mUTkx15IOfwlL8fIT7poa6SHuUlerQeShry5eiDft6sn7IhjUSZM20A6GGVF2nZ2pXlzdvFdtd6p1JfLH/WlbFd3rlyYK5f8ndrFcdJFHvJ3WnenpIxqXam/07ZH+0m3pds/WUZ7qJM6qBP7mXuxQIY4aCdKU7FDPvJj80T8Hm2PdlMGcz8YcSj6lL/h4/BzWh9/q/1DHhjfUWbEubSOTvyd2kueqr3VcsK/fBfjI45TVif1tPNLlBc+ST/n2hFlhj2kTX1R9Qd1j1dO2EaeNH/YEH0TdUZ6/lI+x9OyJ2InTMuq2lkti3Thp+gDjqXpIw92dWrvzky0FZtiTa3VkWCDTzPuZnymcV/j84wvNB5v/NOenoFP5CsTnQzAGNhVxrFcvm5xsvWneSIwVhkBI62D74Lj1QGreaPsCGjj1VM9Xi07LTfypGWl6VNG3jR/ylw5kWey9VXzp8z5I8rNlZeyWm7VrlyeYJo3zd9p3Z2Ssqp2QtodjO/S+juxoVouf7dEG3IMG9P6Y6GMBa7KOBYL31RtTW2oMo7l0sR37cqK/6dM8wfjWFrOWJxIWWna+H96fCymeXNMy6t+hmOVCavlBcfKHxyrjGr++Bzp089pmSnTNNXyU3ZazmTyRL70cy79zsqZd5vGOtX48kJzsVmGBkOLocnQZm0F2zOM+xifazzC+DLjKT09/3Nh2eFinelgrjKXvtvM1RvMpRdFsXtM51uItlSIQsRZ9btUrE11rqY2VDlWmrSMsdKNx1w5YzFXRnC8tNXjY7GatxPmyqkyly9lLk+VuXzBTtJW0+SYy1dlLl/K6cqzsxFt1fNq4x8ZjzSivdBg4wq2XY0Itr2NBxsPN77EeJLxL+xs8Df5CkVRFEVRFMXOOf9xk1pnmL462fhS4wuMzzEi2NBi4wq23Y3PNh5oPMx4nPGVxv/W0/Omm/OViqIoiqIoip3z/H9ybdVzYqG10FwHGdFgaDE0GdosdFoT/AcFt4uRm9z2NMaTovzaQfHgQc9f9fTc+NN8xaIoiqIoiuL4REsd+FbTVfHAAVqLV3rwS1N7GdFiaLInd9cCIdh4GoEtON7/wU1vXEvlmipbdVwW/fOenhde3tMz74n8tWlRFEVRFEWxPdFQp8w3TfUXxrgcygMHaC6eEEWDocXGFWxswXGzG1tybM0933iMkZe6oQT/0sqelTdCFEVRFEVRzBOx9mdrTEv9lZH3r/2J8VgjWgvNxTMEaDC0GJoMfVYSbIAvuFaKouPaKZdF431s6S7bG4yn9/S8ZLCn5/qH8gaJoiiKoiiKLaKZ0E49f238cyO7a7yJg921eP8a2gsNhhaL+9dqSHfZ2IpD4cXTooca4142Hj9lG48nG87r6XnT7f5IuiiKoiiKoljm3CdcK+0zUGin/278UyO/bsAVTB42QGuhudIX5o4r2NKnRbmOiuLjuiqPm/IUA5dGqQjRdrrxHOPbe3pOfU9Pz8Xf6OmZ9WjeYFEURVEUxR2dc/+jp+e6n/f0XP49k0ofNB12temkc43srCHWeFEuWuoPjbzvlh8q4EHP2F2Lp0Nr96+lqO6y8R4Q7mWLJ0a5NEoFIdq4PPpG41nG84wXGy8zXmHEwGuM7yg4UxRFcSfitRNgLr8oitsHQ+egedA+aCC0EJoIbfRmI1qJy6CINe5be7ExLoXyZGjcu5Y+bNCRYIt72eK3RSmI97Kloo3Lo9zTxk1z7LZhzJnGs40oyfONbzNeaLzIiOGiKIqiKIo7EtE4EM1zgREN9BYjmghtxK7a64zcs8ZlUDQUYo3XeMSDBlzRjFd5jLu7BjiY7rLFpdFUtPEQApdHue7KzXIoRYzgCVJ23P6H8S+NbzL2G9kChFy3xXhRFEVRFMUdgWgbiM7hNjG0DxoILYQmYlPrFCM/QMDPT6GduAyKlkJT8asGiLW4FIr2CrE2pmADIdiqoo0CEW1s3XG9lUdQjzJyXxvCDdXYZ8QwtvwQcCjKPzPyJl/4elEURVEUxR2EoW/QOmgetA8aCC30KiO3kCHU2FX7AyM/+ZkTa1wKjQcNxt1dSxHKLrfTxj1tPIjAEw1UinBja4+nSDGI138cb+SSKSIOY9mFgyhMURRFURTFHYGhb9A6aB60DxoILYQmQhuhkRBq3FaGduK5ALQUmirdWZuwWAuEaKOAEG1cX+WmOJ5kQBlSKZWz48arPzCIrT523o42Yijbf5AXw4miKIqiKO5IDJ2D5kH7oIG435/bx9BGbG6hlbhCiXbip6fQUl0Ra4HYZYudNm6Gi6dHUYZUymVSdtwwBIN4BQgCDiXJDXUYG+RdI6IoiqIoijsCU42D5kH7INDQQmgiLn2ikUKooZ3QUGipEGuhs2KjbNKIAigs3W2jMtRhiDd23djiQ8BhGL9FipGQnbiUiDtRFEVRFMXtkVVdE3oH7YMGQguhidBG3KcWO2rx2o7qrtqUxVogJ9qoMIQbl0oxBIMgAg4DMTSIshRFURRFUdyRmGodtA9EB6GH2NQKoRY7altMrKVIhVuIt1TApSIuhFyVGC6KoiiKorg9s6pvQvuEOIOhjVKRlgq1LYqoJBiVVwVclWG0KIqiKIrijsKc5gk9lBNpwWlFtfJgKuJSpg0QRVEURVHcnpnTOsGcPtpukDNeFEVRFEVxe6cgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCNsBenr+P/GJbf3IDe/dAAAAAElFTk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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b,2)+c;</text>
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  </question>

<!-- question: 361129  -->
  <question type="formulas">
    <name>
      <text>L62 - (a+b)2+cd</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b})<sup>2 </sup>+&nbsp;{c}({d})</h3>
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      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>({a} + {b})<sup>2&nbsp;</sup>+ {c}({d})</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td><br>
                <p><span>Add&nbsp;<span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}({d})</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p>Exponents:&nbsp;&nbsp;<span class="" style="color: rgb(51, 102, 255);">({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p>({=pow(a+b,2)})+ <span class="" style="color: rgb(51, 255, 102);">{c}({d})</span></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span><span class="" style=""><span class="" style="">Multiply&nbsp;</span></span></span><span class="" style="color: rgb(51, 255, 102);">{c}({d})</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(255, 204, 51);">({=pow(a+b,2)})</span><span style="font-size: 1.64062rem; color: rgb(255, 204, 51);" class="">&nbsp;</span><span class="" style="color: rgb(255, 204, 51);">+&nbsp;</span><span class="" style="color: rgb(255, 204, 51);">{=c*d}</span></p><span class="" style="color: rgb(51, 255, 102);"></span><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(255, 204, 51);">{=pow(a+b,2)}</span><sup><span class="" style="color: rgb(255, 204, 51);">&nbsp;</span></sup><span class="" color:="" rgb(255,="" 204,="" 51);"="">+ {=d*c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};
d={1:5:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b,2)+c*d;</text>
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<answernumbering><text>abc</text>
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  </question>

<!-- question: 361130  -->
  <question type="formulas">
    <name>
      <text>L62 - a - (b+c)2 D (de)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a} - ({b} + {c})<sup>2</sup> \(\div\) ({d} \(\cdot\) {e})</h3>
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    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p>{a} - (<span class="" style="color: rgb(255, 51, 102);">{b} + {c}</span>)<sup>2</sup> \(\div\) ({d} \(\cdot\) {e})</p>

            </td>
            <td></td>
            <td>
                <p><span>Inside Parentheses Add:&nbsp; <span class="" style="color: rgb(255, 51, 102);">{b} + {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p>{a} - (<span class="" style="color: rgb(51, 51, 51);">{b} + {c}</span>)<sup>2</sup> \(\div\) (<span class="" style="color: rgb(51, 102, 255);">{d} \(\cdot\) {e}</span>)</p>

            </td>
            <td></td>
            <td>
                <p><span>Inside Parentheses Multiply:&nbsp;</span><span class="" style="color: rgb(51, 102, 255);">{d} \(\cdot\) {e}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p>{a} - <span class="" style="color: rgb(152, 202, 62);">({=b+c})</span><sup><span class="" style="color: rgb(152, 202, 62);">2</span></sup> \(\div\) ({=d*e})</p>
            </td>
            <td>

            </td>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);">
                        </span></p><p><span class="" style="color: rgb(51, 51, 51);">Exponents&nbsp;</span><span class="" style="color: rgb(152, 202, 62);">({=b+c})</span><sup><span class="" style="color: rgb(152, 202, 62);">2</span></sup></p>
                    <p></p>

            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png?time=1624662812978" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"><br></td>
        </tr>
        <tr>
            <td>
                <p>{a} - <span class="" style="color: rgb(255, 204, 51);">{=pow(b+c,2)} \(\div\) ({d} \(\cdot\) {e})</span></p>

            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p></p>
                <p>Divide: <span class="" style="color: rgb(255, 204, 51);">({=pow(b+c,2)} \(\div\) ({d} \(\cdot\) {e})</span></p><span class="" style="color: rgb(51, 255, 102);"></span>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(204, 51, 255);">{a} - {=pow(b+c,2)/(d*e)}</span></p>

            </td>
            <td>

            </td>
            <td>
                <p>Subtract <span class="" style="color: rgb(204, 51, 255);">{a} - {=pow(b+c,2)/(d*e)}</span></p>
            </td>
            <td style="text-align: left;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr> </tr>


        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={10:25:1};
bcde={[0,2,1,1],[2,0,2,2],[0,2,2,2],[2,0,1,1],[1,1,1,1],[1,1,2,2],[1,2,3,1],[1,2,1,3],[2,1,1,3],[2,1,3,1],[4,0,1,2],[4,0,2,2],[4,0,16,1],[4,0,8,2],[4,0,2,4],[1,3,1,2],[1,3,2,2],[1,3,16,1],[1,3,8,2],[1,3,2,4],[2,2,1,2],[2,2,2,2],[2,2,16,1],[2,2,8,2],[2,2,2,4],[3,1,1,2],[3,1,2,2],[3,1,16,1],[3,1,8,2],[3,1,2,4],[3,2,1,5],[3,2,5,1],[4,1,1,5],[1,4,5,5]};
f={1:10:1};</text>
</varsrandom>
<varsglobal><text>b=bcde[0];
c=bcde[1];
d=bcde[2];
e=bcde[3];

ans = a-(pow(b+c,2))/(d*e);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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</answers>
  </question>

<!-- question: 361136  -->
  <question type="formulas">
    <name>
      <text>L62 - ab + c(1/2)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;"><strong>{a}({b}) +</strong> \(  \sqrt{{=c*c}}\)</h3><script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) +&nbsp;<span style="font-size: 0.9375rem;">\( \sqrt{{=c*c}}\)</span></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">\( \sqrt{{=c*c}}\)&nbsp;</span></span></p><p><span><span class="" style="color: rgb(255, 51, 102);">Since {c} x {c} = {=c*c},&nbsp; &nbsp;&nbsp;<span>\( \sqrt{{=c*c}}\) = {c}</span></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> + {c}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                    </span></p>
                <p>{=a*b} + {c}</p>
                <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} + {c}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:11:1};
b={1:11:1};
c={1:12:1};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b + c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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  </question>

<!-- question: 361131  -->
  <question type="formulas">
    <name>
      <text>L62 - ab + c2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a}({b}) + {c}<sup>2</sup></h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                  sizeN              size of the font w/o px, e.g. '14'
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) + <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">{c}<sup>2</sup>= {c} x {c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> + {=pow(c,2)}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                        </span></p><p>{=a*b} + {=pow(c,2)}</p>
                    <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} + {=pow(c,2)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:11:1};
b={1:11:1};
c={1:11:1};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b + pow(c,2);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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</answers>
  </question>

<!-- question: 361132  -->
  <question type="formulas">
    <name>
      <text>L62 - ab + c3</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a}({b}) + {c}<sup>3</sup></h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                  sizeN              size of the font w/o px, e.g. '14'
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) + <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">3</span></sup></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">{c}<sup>3</sup>= {c} x {c} x {c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> + {=pow(c,3)}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                        </span></p><p>{=a*b} + {=pow(c,3)}</p>
                    <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} + {=pow(c,3)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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xPO+2filBexvr1n27sttubjeeYELvCgvxNFuTnG5c2HnnkiSJVGWeddbOlRSwh7hZa+cuNa0r1dZdrGtdcUxVsvzIbLmxy992vMTvmGBdb2tXN9PlyOmFdsHk9F1g9V1kd+GeRpaOe1VkRfPXVH7O011q62YVN4Z+wK/5PGauMKwvy/zRdlWsmWZ+4Y9H79uabv1mMgDzWr/+8jYurjbNsXCyxPCuezJsvVxTFnZGmsbor2HbffcgCjzg5rml88IP5n6I6/PBLG7vu+hbj20y0zTBhMte42PKsaNx554NFqjLuvPP7RfprLO2gcYmlX92sJ1//VLnGRMkXitod9933S7PhvCZ32+1Ks+Em4yJLOxU7yFcXbF7POVbP5VbHLONCS0c9qxrf/e5vilQtnHnmeyztpcZrLe0849IivduVPjxx332P2nfLjKRZYVxlbNeG1ZOqT9wRSd8ua3tSFbjzzh82jjhigY2J2cYFlme5caVxWx4f2AV9jrWoMb31WO0PxpD6ZEehaazuCrbddhuyBUmcHNeURELgnnt+2nj6009v7LLLucZLTJRcZ1xo6ZcZVzfOOmukSFnGww//ztKfY7zc0s8q8qxq1pOvf6pc07jqqrpg22WX8wpeaTbcZFxkaVc30+fLGY/kqws2r6PaXupZZT66w/zRWjQ/97l7Ld3FRvw50zjP0i0p0rtdVey66xzjbON8O77UuPLJtGXSJxOvT9wRSd+uaMyf/5ViJLTHww//e2P9+q/Y2GCOMHYZY8zXbXOMPP64vyeSv2ed9XH7bnnBiDEa19PLNRZvWzv7H//4/fYdY4g+WWHckrFfnA6axuquYNt11yELNuJkeOaZnyqmWhnr1n3GBNsZxgtswb/CeKOlX2JcYVxjXFoSBynmzfuo5bvE8lxrnFvkWW3M2zA1rmlceWVdsD396ec1iWDbZRcXbG4DtufKGY/kqws2r8cF2y67uGDzelY1ucsuC4w3Gq+ydBcaLzbim5lGfINPw66cIJxhvMZIGQsszbIn05bt8zonVl+aX9yxuNK4rPG1r20uRtLYePjhx23Ob7AxMsfIGI65zjjeVsZLeX5ceeWnmmN6l13m2zHsDVtzeTtlzK2UuXQ7Ojvzw5VXlm9HYU0g3nqsYRwRrxRvtmeaxuquYHv609fYoiROhp/7XP2nqMBhh13eeOpTz2w87WkXGWdY2jnGZcaVxtXG5Y2PfSz/g/AbNtxned5mvMp4k6VdWuTL2zA1rm5ccUVZsG3a9Eur99yCVxQ2LDSuaqbPlzMeybe6qKEFr+OtxsuNN1qaBUbqCS42zrVj1xuvNl5jnGGcZd9jEz71svPlX2a8xPgOO04fUF6uHXyeaH1pfnHHImNhhXG+ibb8HM8B4faBD3yncfjhlLHIGHM3N+amkz5mU1xxxYiN6+uM19uxecblxqnEmZgXtDUY3+XS76js3A/V2Mv48bhPv8y2NMScGD/lvOL2QdNY3RVsT33qGhMX4sS5+slLDCk2bvxJ4ylPOct4tvFSS/dO4zzjCuMqI3lXNE466UNFjjIef/z/Ng49dEaSd6FxmXG1sWrDVLm6cfnldcH2lKec2+RTn3qF8SYjNmD7ZG0gX11QeT1vtWMI3BuNC4zUE3UtNy424j/smG2cYyQdPllp9LLz5V+QtGOWsV07ooxO60vzijse6WPGCWNhrp2Y5U+u2uHxx//LTsjutRM3xsv8ohzGVjpec/VuKXqdKS6//Hb77irjDCPjfKkR+3L5x+aGDa0nrNeu/aZ9t8RIm2PO4Mt83h2JDz/st8fQ/6efPmLf4Qf8St/n4s5Ki7ePNvOAD3zgmxavBux7+iTiYbpuiNsbTWN1V7D19FCoODGubgwO/ksxzcoYHLzdjp9lPNd4pfEm40LjKuNqI/n5//LG5s3/VuQqY2jos3b8QuMM4zzjEiN5I38njPTUtdK4ouDy5P8rGgMDny9qdSDY3HZ4hTFn/8TrgVV4HW81Xm680bjASDlRF/mWGRcZ8QOcb1xspHzqI53XW0Wr/MuM7zTONS41UiZlk28i9ZGu2v6UOV+Qr8q07siTKy9YLZO/af44Fsej3vh/mjZXfreYsyXX9qpN49mVlht5I38wrS+to5PycyQPZdH3s21ej9pC/J/FyOoM7JgMDX3N8g8aGVOMvbB7MjZNlu6/FAMD/2DfXWKMuUeMwWe5/GNz06bWfVgjI/9q3zHPIHGD+RT9kM+/Y7AsiAcGPm3f4QPiB77N+YDv8M8c40wj8fZi41XG643EH8Yg4yXNJ24/lGDbBri6dFYZIKD39PQb32IMwcWkrQouX2CGh79b5Cxj48af2vHzjO0E33hcbQvFd6yc35hNrV1A7pHYsOFnFkxGLQ02LbX/31kcdUxMsK22/F+wMn/+5Nkl4Axz48Zfmw3ftDQseC6Sqmgv2FY3+vs/VbJ9dPTH9j1lQV8E0oViIujvH0nK8YW9k/rG9r+LeHyxefNvi1Ja4EyaMgcHv2Jp8T1lEozHXsDpxwD29fbeat+7P3t73908jh9S26mfuvr6PlikHb+eqbK3971Pjrl0LADGA+0fGbmv8H0qmsOmvF3pPKMMz+v5R0but7b+rjjq7aaOGNutdk+2zeSlDMblbGvjQiv/nqK2zrFp02+sL95lZbAwM5ewLfojV2+3Sfurgu3v7bu3GweMNxjxWTcE2732HSdH1xlpL/MHH26Zcbdt0MdvioGBj9l3+AHfItrwQbW/+Rzja5YRn7FmINbwHSJ/OseJ2H12XbD5YBM7Z2/ve4ppWQb3n7lgO8fI2SsTkMlIgE4XJv6/0oL4B4qcdfT1MckvNTLpOdOq7hjkuKopGqoLZg4bN/7C2sEOW/nBCRds2A8RUgQS2hCBw+vq77+jFKjbgV3E/n7O5mcX37TgdSDYYtGgzdSzsikEU2za9LB9jy0ISNItLY5MHCMjP7D8CER2PnwBre801uvzPqj7HKHSic8D7LwMDNxheakf37JYhrgoj5ORkQeKXA7Px47PXU0hNB58AZ1tZAzF4lmtZ/JkLiCcOrElgG/7+t5r+WMXJnxbHd+ramOMPuntXdkcV+3gY4l+o83h28m01+epi0sWT/x4rdnOCVu5X8YDJ3P9/X9n+avjqTv9MDa9HSkGBj5k311kZPcZgUD78FMu/9hML+uNjHzPviNuMKeJf9EH2DAdbd0azPn3H+07/HC1kT4PQVzNx3fMS/xEPCBtOi+6N1fFrUEJtq3OoaFvF9OyjMHBD9vxvzZeYGR3ClGQnmGmZBIuMeH0qyJ3GcPDX7bj7NJdY2ShaCcYWkx3YzoBryUYHv5W8cnhgg0R1V6wIdbSHZ3xwGI1NFR/TYLX006wVQXUb+x7fPEOI0Ftodk/9ruy2mFw8FOWn91LFhS/XDV+fSxoLNxp8FxV2gGaKIaGvmpl4N+qsIg6coLtI1bnT4pPnWF0lBMJFmXaGjuGaT2TI2It3eGaCBB4/f2IBsZ2nNRUBUxdsPX2zrU6/0/xKQ+feyyUMaamIhjIg134jEUUH+LLq82Wm6x/vtMc353ARdv7LW9cnmdMUXZdqPp3HGNM8DfS5doQbYs81fR+LEVLsMVJIW0LUUGdtJe/UX9aVsryfVjsQPrOHZf2mD+pQM2VVbW5yrBhLDuiDNJgdzCXr+q7KtPy0vpz5UWZfC5fQSjvYBJn8EGsBWl+iG8YC8wDxkV6EhdtHMvOsGsybU/LSRm28f8oK2WkaVeu6JRg2+pMA1SAhwV6es4wnmkkELK1zbY2k4fBnStruS3a+beqb978iB3nsiiiiYVn7DPg6o5UAFE2OvrD5sLCrgCfx8KmTb+w8rikmxdsXPrKiTUWow0bftSsZ3T0XrO/7qMqvB7YiWD7lX3P4tIKgH19w5bus8Y7jPV32w0M/K3xfcb3G//O+CFjeu/OtUa/TFW/NJzWx4IWiw4Bysnlzxw2b36s6YORkY1Nbtz4UNtFfWjoS1YW7YnLZfQxPqBf64ItV87GjT+zdPc062rn94EB7q1stbcVcOtjqROOJdY2bfr1k21nPODLHFzADFt5CCAWKhY07IpFoC7Y8G2KaDtjPMZ2q3/xa5Qb/VZvy/iMvNjGGGA+4EfKv8p8cWOzne36OAVp+vq4VBKirSxU05MhRK1f1mbxTtOV25GeNIyO/sS+Iy2MseRMkQo2Thw2bXqkOOIgxvktDcQd6o845vVP5ISNEysfc/SD29Xf/8niaNjsbRwa+lbpRAw7+vrYmUxt4OrEP9rJ5r3N8ZHu7vL/sL239+ZavqrvUjKmo8wUcYuBX86Pvii3oRNs2PCQ5Sv7c+PG1gu72/u7bCdjZHT0p812psBvbAB429db2patubZTTiAdN319f9/8nN7aEbfTcFVovHLFlBJsW5UEihw2bNhkxxFrZxtZ6GOxKAe6MpfbxLqlKKGO/n4mHWeq3JCa7hRU7VplE6p+SW54+F/sGDtYiCLs8p2z4eGvWmDLLy4u2N7cTJcTbLkdJYRaby9n09RDXhd8iCReBtwOrbRclhlPsLHzd77xbUbqYqeD9CwE2HhNkbKFnp7TjVyipl9oOwKY/PiUOmP3bEFGsKX1xb2IrYWfwF4FYqKvjzTcm0e73N9xTyB+r8IXcPowRBt9TCCknpUmBO4vUtaxceNm8zv5sJO2eT1DQ6NFihZI621GtOE7Ai7jsjqWOuGq0kIT8HGAr2hzuf18v2FDvS0ITN/tDNEW88XrqS6eAfw2MICYYTeb9nvbvX76jN2NOGliEZzqwuL94bbhO8rEXsYePo0dt42Fhe3hJwPMrbjdgT6PcV8+8fJL4LSBuqiT+knbsi31EcLL00PmbWthTYFg6+9/V00AV8GlZy5B+5hhrnl5E4X3L3ON9rKj3ZpvbvNsGx/59975ZX38PNdsWW/pflYcGRvceuC3Y+ALYkWcEJT9R99ydaITETo6+oClp7x51obPFt92Br/NIr0VY4l9l+5O8sCGt9P7mrng8QY7EZQbM/MuB4Tr4OAXLB872NF2yqPtXl4aY2PcjIzkf7knhT9IE+Wm8crLFVN2XbCFo8XxyYMC9YUaDAxwTw7CgAUqdowITkwSBjSBokqOcVn0l0UpZYyOcj8ICzFPDTFB0p2Rll2Dg18rcrQwNPR5O0ZeFk4Ws1SoXGaB7H3ZYO2CLQQO7YiHAVZYwHh3kaoFFmlfMKMeFtBWPSxi7DDl0BK4pCWg4y/3TV6wRflc7kqDMAHuhiJlC77jySVq2hL36+BLFnJEMMGxvoCAfH2+8OOHanBnV8l9TP9XhSF+ZIG+zPqlvhPqPiQNCz9tiYVlRVvB5pfM8XlaFztL1Hep5avfHO+X2LEDX8diXh5LnbDaNwCh4r6i/YwH6kI0Rfvhpc22VuFjlcuYYVcImBXm1/yOYX8/L6VM209dsSOKAETUxxzEn5Q38bbm6bb5/KVs6mB++o5bfz+7j2PvMPsOF20OG4kRy2u+5RK4n1hQdgjtdIEsX5L0S/mMb8j4dmGAvSmGhzc0RW8n4BJ0by9jn/Lon8U2p39tdT3SZLrDxQkaMcT5S+OvkvGNTbR3rrWrdVKBkNmw4cfFpzpGRr5redjJXNLc6amCNjvrP9pPG3lYJOptCYzWWJjorSTDw+yEXW8nWu+1OvHBw02m4ApJ1Q/Dw3dbvrgVwwVPWbBxby3jlnlAX7cE+mRvPxgaIk5Eefgh1iLmcSqa6YPOb7UYGPiolUG51ROJGJeiU4JtK3JldicLbNr0c2NMToIZAYSJ7EFtLHImmAPBzxelVNC0JlyQ4JnCz+ARQkEWNAImwYCzegLGtRYEuB+oLNpoRzvBNjz8gyKVw4NhurPGgs2iicChjuA1FgweLHK14IIK+8gT7aNt7QRbiCFEFwIKu2LRnF+kbMFtoi20n0CJIOIsn7wEmljMlpWCF8jX54JtbD/QHvxAn4UfaBsLBr6fWVucyO8iJ+57RIj6Ap4TbEND/2zH2Dnk9THYiBglLwti9O2iInUL7Hi2nl4mgE9OyOTHG20PhjCkHtoc7ce2GTauy5fl/alo8uCv9MQkL9i8/W8yxutzEGv0EcKGuvBhulMRwrSbCwplYSP9xBjCZnxKvfm5lcLbjMhm3DAmYxxWBVt68zplh+Bo2VEWbJw4MG8h/g7B2n5XDLHNCRxjtrd3lvn3C80xmcLvTcPW2CHCry5UiXWBkRHEDHMOMjbp17hEnRdsqeDDZ97my0wQMdf+xf7Szivs+48VqfwS3dDQBrMXGxj7zDc/QazGGred+R+XofGHC4yqv7GFByf6+jjOuLrY0vxvK7N1ouECMuY24xWfvLM46hgYuM2+wwfEIOY2ZdEnjNPIVxVsnKATC/FTiGOfB1WxhogeHPxnay91U/bbm3bmTo4HBri3mhNUxhnj1OdDNeYF6PuhoS82fYlP+/vfWyvX53y0hfFQHZeiU4Jtq3Gi9yx0A4ODnGET2FmMEA1MNiZxy6404IGhoTvtewIFARPxQLBkYhEECHAELSbZjTZpW0EQIDp9IawLtupC7WfOCBTSImwImgQG8lBHkIlfDmjAAxr5U0HqAaozwRZnjL5TWUVLSIb/IgiSj6AduxXsbHQu2KoiouWH8Dd+QxyGH2gXIoz/z7FxVH9p8sAA94awsOG/6Gd/dUUKX+jxG2I3xAqLB/7Dz9RB385pBvUULthYPGhPBG9fuNLxNDbLl9ZAa7xhDwt0XOKkDtoe7ceu2bYIlx90Ae47/BbjwPul6mtvf+yckifajxBgEYy66Oe0j7sp1qoM8ZbuuN1ki/7NNeGTwv0Vt09g75LaOPTLvgjy8A1jkHqi3qpgYyGlDyACK8RVXbBhW3//WjsW45YTG8/L5dLUdv7f24uPw9et/qwLNuJHTrAxB+uCLcCuZG8vYxO/ME6xifwudvr61jdPbv0SKT4jLceY3/iI/+PPS5p+CPhl9zhpo/50fJVFtQtXysIG5n7YcFHTJ5Tlt5rQpvAF/XJdUYLDBRt+IC7kBBtzfF6p71xYRryOy+Xc51x+yI2dMK+fNoWv+D92X2zpq7GTMUH6WEN83g8MfK5I0QI7g319HKftUa63P/Up6OtjHKY74y4E6/NjZ2bXBZtPenF8ciPmdMPvjWPixOWT8o5BTkT6fTwsaky6EAEs5BHsg9xs/+kil8MFG4svYocAE8F5eU0YDg5+3L6nHgIzwYIFgoDA5E3rod52O2AENIJsnP2OJaBCGBJ4yzsx5KnC01fLxx7qiHzOzuur1+OLKgtU+JvAyGJG+vABdfKXvptb21X1hY5gHf3sYqMq2FoLIiSQpgsoeaIO7o8p30g+MvIt+55+ze3Y1sd7nXUhDdxPtB/7GTP4OrUn2o9diy3Q/22RswUeDGmNIYQeZ+xLrQ1lwebpqAumi3AItLS+tJ9z7ekmqSP6GDto/yzz+fcLy+vo719naejDEFb1h198bJEmhB1jKua/t60u2OgHyNhg3Pp8TOFijfoZRyz6+J5xgaAg3zVme/k9kYODn7Dv04Wf+YToaF0OHBn5tn0X8w67Y+eXMcEJE3m4Z7Qs2LDHX2VETGAeIcLCHvJzAkQ/0x7KYfzyPeUzBrA50s2s+b0ljklDGUus/R8vjjp8h4sxBfEfbaX8KJu/1BWM2yoYr+XXFg0M8DANfqBeyqGPow34jrYuLPWd31ZA25lD9DVjYllzNzFA3OjtxX7sCzFFu1IfXG3llk+u+/t5fyPlYgP1c3JQ7gMXzIhFYgR2MCbIQ9nXNHf0Uvh4oJ+okzKJ89M137YXSrBtJa6oCZbpAE+f9vYyETlDI0Aw0VnMfFJUF1AuN7mAqi5oBPrIF4sZ7x8r3zjrgo1gS7AJweYLexV9fUxQ6kFQVhfqqMPr4bsqvJ5uCbbcLx3EwtFOsLX6trP6Fljg+0SRogXvHxa+nL+jrtTvBOqqmEKIUReLFLZ6/rxgi/6JtAR26qJtUc+yTB0Itpw/Ul+Mxfplcd+9wJbYyQzBxRig36PtLbvwYxUuxFiEUsFavikbeDrawKJCO2K3Im1/lbm2bElSp/dzTpwGfBeGBZ02s/DPt+/Kux6+K8q4YtHvVLAxHyFix8ctvkkxOMgTj/gx5i++pO/wPbbMNtv/pkjtGB3lHivSMsZDfC0ujTOelvU0tCuER9hAvKCf6i/s9l93YQxhD+OAvLErTn7qIg4RX+hvvwzpafhLuhBC7OCVT0R9vISApI2LzNbyT475ZVDGMvUzlpnXpGU8M8f4y2fqIxbzf77HroVFKY7WbnZ6EkIb8EHMjepDBwg2/Ma8RlgN1kTl8PDX7XvaQXsYF/Qbggl/hJ9usv4trwvDw7ywu9z+auz3eM7ONeMC27Ej2knZ5fuEXZwTsyiT+vE9435rzLltlRJsW4ErbALUb+yfLgwNfcZsIIgQQAhKIVTq2+UuNJjMBL8QeeQhQDCZyu3KCxXyE7hago1HvavwNARYAkEEpVg4y/VQdxWevyogsHFLCrZcQOlcsFXTgby/8UHV38Gltvg9WOR2uFBGaLNQhDBfbEExJ9jiEhbjgQWjembr/88LNuyMxR9/TEywVe1pjRcYArKdn70Mxkj11yBagjX6ygVrXbDFzgULSgiSdBxU69saDFuYC+WFPIULNtrSmmfTJdi8XOqGlB2LPuKD9NQzWDpJ9b5m7MXJGWOPXdBUsCE6sJf6QxwwHlyo+Xir3zPaijmQMcAccBHrtiBygtiHnSGimG/UEbbjx6pgo1ziFLazO1fe3eLeOT9OOuYgcz7GcohN/rog9DpdqPmx8i0ZrSeYKQtRSZ7ou4gN5R3knGAbHi7vFPb3v9u+p9zYuYt+S/2EnXOLHA6e0PZ85KFsTg4+Uxx1+PzjxJO+ow+wm/ETts8tjQcX5yHMJ7NjvzOw64ItgovYnsttwOffuTU4yA2yf2V8o5EbwTlD4TIhQmZi5Ifjc+B7DyStwB6BL7+AIlJCQMQWeASKcrvaC7ZYgJmInLHW73fwNExwghKBg8md2+lgEo8l2KoCot1DAKQnQLAQEKgJTF72xMqPoNKyr7P66jsgoOXvCIa+kNXrCXKps3x274KN+ljs8KUHyfaCjXSIZNKxYKR1uT/ygo3+qo6LdnZWWX8Iov2ObM7Pwdzl2m/Y9/g6bPNFMi/YcoK10zZMJ/FB+1/k4B2BrXHjAmigcpnKhRVtTf3CHKP8ej/7uGXhjRMNH7dVO7xc/M3iHDtmnq7Vd/g/LRsxSF9jS8z3nOgIwYZgrM5Ttzsv2LCHtkY+7Albgu5TfMB70YaHv9c8+cEGpz/IVf0lDC8/FSwLmukCLaHLOEasxPyIeFav38n/3WcpXLDhh1y/BXO+Y2yHYOU1G+U40epbGDtbzLe03/jLSVHLB61xEfNmjtlYFbW0n/6N3UXGhItRLze3m5r6a7y4tzNSgm3a2dtbvjQQ8JflItZ43xcLYSyknKkx6CfG6s2iKfr6WJhJx0QOYVS/x8knJpMOMpHiLDEmc9q2bgi2ToQKn3d0wRb+dn/l6wkus0Wm/KSo/6wZ9aVCZEGtf12wYROXWjgDZlHjrDot3/2RBldQFmyxEziRADuWYGPsc/9LLPxuQ76cpbUdNn/ykzJijFNGO8FG+5ljiAYWq2r7txXS/m1ZsLFAx+44Y4FdlOg3WF6gW4KNPmrtqHdHsDH2ycO4jhOWEOKtfHBw8Ku18TMe3M+UH34s31PrbcNnjMHYMcKGdH6ELR6jWnPc/5+iO4Jtdu1BLz9OOyjbhVe538LO8i0R9XExy2ws/yyhjzP6gfGYrjPRzvKJVl2wTTSe7AyUYJt28vbtHPyBAHbWWASZCAx0JhEBhwE/UV5jIjD/VNnwMG/EZ0IRBDmr8jOfauAjf1lAdEew5RYef7EvgTCCkgRbp4KtKkRciFHf9ijYGCssJPgJwVZdoKusjyW/PDhRwUb7t23BVh1XKXxHfmsJtlRQhL/HFhQtwcbYiziEqOuWYCNfzNWcwFnR9krHeCg/Ve3tTdHyW8z3Tk48ghzfMoKtOv7dT/g2nSe58c+4qPYd7aN8TqxuMBurgg17OZ4K1jSO5ezFnrBXgq1OCbZpZ/UsJzA4yM/9xI+9MzE56ySIEaQYvBPlLAtIPy1KL2PzZt6SHZOZgOYTNbcg+KPxnQiIqQm2wUFenpheYtvxBVtv761FihZcRExMsFVfAOr3KVIfizPjaNsUbOxuVDFRwdbXV3+tSV8ftlBGp4JtrPZPhWG3j0P3T/Rlvj3tuaytwPD5zM484ybdyd4ago1ySTMRwUbZ3RRs9D35Ir7VBc7g4IYitYP7qYaHv2FlEYeZ45D2+DvJUtQF27zMJUOOx3zv5MQjyPEtI9iqO/E+1zoTbOkupPcd+Sh/LMFG+9N70tI4Np69E40nOwO7LthiQIo55m62B345lJd3EnQJqAQw7t9hYsZ1/4lyoQWlLxU11OHvTGJSxSUMDwJV1IVUTKR04YHLaguwBy6CMoGBiehn/tRTFQCjo9+377n/jgDOriLBmeARk7ZVT07oeB2xw0CQDsHHU2Tlnaz8Tg7BKhbWcsAE7cuv+6Gz+ghg9bet+y9SpDuN7fzt7O8vv/sOuGBBsMWlvhBs5XtYWoItvSSYXjqC7o+8YKO/CPaIneolj/G4LCu2fLzhq7LAb1cu9x2l8BdEp+9VCwGRE2w8JTpe+yfLZU0RQJ3+u5GUC2NMd+onZ85XgeHhuywNsSP85jfn1wUb7+djoQ2hEQs0ddT7OS88fNymKAvBarnBJU1/BPznzRjn+J6ysbn8xHNZsPmlt/I8dbur883HflWwle0p/7Zl+noL6qK9/KWMC638nGBjfMXYn1uy25925njqt6rd7cjxqiDuzL91AYQfiFfYyE+dVZ9kpRzEeLSDvq2WC8vx0C9fko82uiDjZ89SuL1xPK7MpON+PHsnGk92BkqwTSOXWWAtv8YgsGEDv/sW967F5AnBEoN2oiTvwlKQTOHCgIDCGRJnt0yoxaUzReD3Q+UWZiZfq308Ml6tq3VPEgtJKtjqTzb6QksgJEhyNk2Qow3lergHMHfPidez/Qk2fsQ5hb9UlDRj+ztY3bH1xSIEC2UQ4KmLhw62LcFGm6qC1X3ViZ99LNQFL8Kf9tOudMGeXsFWHQP8rmJvL8fwk/dHq1/dx7ly+J4TlHb3WfmrejjJoS/SnbB5NTHvr99AiKTjIhZot2Eygm1w8GP2HQt0jAViSdmPVVt80aefsT0uidJHOcEW7coJn8kJthT+zjRsp53RDoQvdl1t5Y8UKR0ep1OhM9fGXfln0lq/g+s7UO63dv2cfsf/2wm2XL8Fxxdsg4NfKY46/PUntCPGf73fsKe6G+nvzCRfjAtemp67h02CrbuUYJtGLmsbdP3pUBYZBmxnOwvjk7xLaoEk8PDDv7Xj6cLIBFlsorL8gkvg9wQxAQma2BYB0INLTqwBX3wJboipEGzerv7+jxapWvCn+wgE+ACbCEwEEK9nrIXL69lygs0XuxDUBE33l9fRygc7F2zYVn6BJHCRjL9JG/7GD2ldS7P3Q/Jj7S58WZjxIz73/NuiYONHqqvwS7rYxP13LOTxioFou+fN/XC37xpgV/jPd27IvzUFG0CM8xLWvr53WZrY1a6OobQcH0tVUZpiZIR3afGwEnMs2sHYp+yysPLXMYRgo8/S9i6rjadOBRvt8peppvXj81Z7qn3l6UOw0c+UXX4wgZ8w8n4kJuTmactHKcYXbOX5PTj4SfsOvzBHaQN1McepD6FzV5HS4elIHzte82ppWi/9HS+eR1tSlgXb8PBX7Tv8MDXB1tt7c3HU4SfJ9C2+Sh8WwYaWfWm5fkJJH9Mn+MBPECTYpoNdF2wx4MQqc5eugF8O/UtjeoYcgYkBngbziZB8PK5+e1FTHYOD/C5c7GixMC6wyThUE1/Y6Gd5MZkIyNjHu73KIiCFCxXEQ1VIMRHrL3wFHpxisfadAurh7LDdbiHwehBUcRmM4EM99bdwu10scHEGTNupJ/zNk4flnUZfvOgjbPP7C/v6uMTEguf1hM87r488/AZg+ceeAT+b1NfHJCU4Erzc37C395as31uXoPEFAZOxFIKlnWDDpgjYBNUI2Ok44n6TdoItdwk7zd+O7qve3jXZfmXB898fZIEKAUL5S8wvH8zeC+o2MdYYB9hFm5hL9FE7wTZe+yfH6hioYuPGn9tY/7al+6S1k5+doW76mPfzfbZ54pSbHyn83rW4lYLYweIYJzq0o/w6BhdWt9j3jI24J8zn18jIpiJVCz6eWETTcYud9RdXt8qOBZr5h995qWrZF/5CboQCY5X52ho/aZs9HaKA+uPkI8r1sQCr5bvNtJGY07ok3uqfsiDasOEB+w57EGKIIsYCIouXzd5eG58+xvB3CF98Un7PnPuDX38gDe1jHPo89DH8d83xyJWG6Pe0XSlcaFNfKqzIk8ad3O5kCKDw7yIra3ORwuFl499qv7kd1fve/CevKBd7IhbmXusRgi1OviPuR3zI3a9YtXci8WRnoATbtLE68AP+dCiCjeAVi1+coU5lsJIXzrfAl/9BeK87nVQEgfk2eeq7HoDLbfzEDLsEPNBQDWT83mT6I9X+4+/tBBuBvPyyxQBnfqOjP2zWMzp6v30u7zBQ78aN5TN236HsnmCrXrIF2IWQIGjFbx5yZu1tikWyvkCNXR9vsL+t5ssAPwuDH0ZGfmD8obX7l9m0LBB9fZRJPSw8+DvdCayL660v2OCC2u5EgDbRz97+e40/rNkR8EvB9H/sZMYCFONtegVbb+/6opYtA8Raby8LZvxwf12g0u7h4XuKHA586pcw3T/4vuqXQH7c5gVbgIW3rw+hcoPZN2SfN9XGq9dPmSzQsQvm87UqHBFT/usfl1h/fczaw8KOuKGffFxX59vYgi0/nv1EMezhB/dX1mwJ5AXbXEtfjpv4mku/fX2r7Tht5L7Cz1ibWrELO3zupDGkLFyB23e+2TVo/vuC8Yv2mTZFX3cm2HKxBmHuu4yMH798Ozj4Zfu+PC4Q0L29tIP2I6QjxuReLizB1n1KsE0b213WGBh4rx3nLDkd3NUzwsmSwb7QxEf+sqjf/8KZdioUPWi0e8K0HRAWvb3XNyd/wAUbQion2DzIDA1N7FcfCBr9/e9pBsIUrXsAuyPY+vqGa4EtB8SEt4uFkrbxuo52P9GVqw8/LLQ2/UMzwE8GCEl/LQq+jss1XNaJBdb9sG0JNkhaxvk8Gwf1J0Y7BWPOx3HcVpDu0DKXqKd8CQZsScGGL4aGvl7U1F24WGM+ETcYVyyOcfmXMUg/+OLY27vWxkf+hK0KTrg2bGidqPi4Ze6m47Yu2BgLnWLDhh9ZfvqIHS3sZhe4NR/YtR4P3s4QOfX55uW3E2yQWxHqJ4vMP56ArP52ZjUO+Eko9qeCjTp4gW59t3wsjI5y+wPzh5ML2oQfGDt3FynyoB6POcQ58vA7rOMJNsbF/HHLzgHf8IP1Hlsol7bHDj67wtVfOpBg6z4l2KaFuftZgN9Hlj4dyqITl7AY3PnyJkZ+IPv9RY11+KLF2aLfi9BatHgMvPwaiBz8LJLJxsJ9gU3CVLAR8GPXI+5hi4kLmZCDFkA2dCRWCPa9vZTxNquzKtioh8UrgvR4gi0WjRA2qWDDb4jJ8QPbwAD3H7KYEbh9QcsLtnb1hR/mWNsWlxbMTsBvMvoOBOXjZ8QHuyf4AF/Tl15PXrBhEwKHIDlRwYbPY9Fqf0/f2KT91HmTLQhcJsq/9iYHxszw8AbLS7tpP2QcMpYZJ/iYhdrbXxds1Rfndlew+UL2iQm1aTz4PWvsyLOzhmBmAY3+Dvu9z5ycDNw+rmhjJ7O398bSvGrN37EFG/OO+w45ARwLo6P3WlrKih0qTq4YO+k4XWTp2s8B+tzjJDs7xMrZ5uOqWGAcjC3YqK+T+e0niOXfcPV4TR0x9hlnfkmTnbkNG/K/MlMFcx2fux9oE8KGuIWtc01Al2/LSEF/+UkGeYjbc0pztL0Aws+I3E8029YJGL99ffiM8ug/+i7GnM97Cbbp4NQEG4nJRGYKMcGGc8UqueemOvnYFRka+pQd52wNoRHBi4HKhI3BOlX6wjE6+oAFu/KZIoLRL6MxAdMdGern+1l2fJ3l/aHZX17sCOb8CHDrPW2+aHIJI+D3R8RiysRlESUgYZOLKQ+miJWFVt7dVm5L8IHNmx+x+r9ndpCuVc/QUEsE+82zfA8jSLcuBfJahbTtbhc2sVinC1HYhN/wwXyr912W/sel9rMw0f7W+87SRRPh8ZEJ1hd+wOZ3WJ1cjvlOs46qkKWt3N/mvqfPWFBh2IGfWcwYRwTnGEdLzN5vFqU43P5UsKQLZ9DtSx9GwabyQxjpuA3/dUrSY6OPNxYhXqOAEKX9VTAe8KfbHm2HLA6IVfzLAoEvy+1PL0XRBn+1zXjtnyypl7Lwy0xr0z9Z/a25MREw3rh9oa8P/yAWiBmMdRZFxh39zbG4DyrtA2yYZ2MFwf7dyjj+z6ZNAwP/YGkQuhfZ/1uvHvKHX/Ar9SCCqcMFW4xvFnP34Vubc5S+YYwGEAWcaA0MfKhIR6wJsUbs4F4x+j78jv1cJv98U5Sk8Et3n7Dj5GXse7v7+z9cpPD6vB7aE2KB8ik3fNLyCz9KPzr6rzW/8MDD0NAXLA11XfzkcY75eGOuEWuwAZ/EPZaMIV5z8ZFmu+tx81fNeNrXxwLMuGP+UAcnXfgiBJvHxeHhb1kZrdtM3LbN1mZ+B5T2IdrId5N9/6siFXP78/YdfuBEGRsjHlJ2jMtrLd0Xm+WlfQaw2/uNscG8or0xVyiT+dIaD8S8gPcB6ehn5mOcqFN/jM3FHdo70XiyI3Pygm0PowRbR2TAQQY2CzWBjwDIAkvg5S+fCUCcMfoE6N5ApRwmKYGA4EWAZ2IgfiLwMxmr9ROA+D/fERQIDkxcJiFBHFIOn7GfAEkAo3zKYuL5IuAkOOeESgQnjrHwk5/Jjk3VeviOYwQ47CEYpPVwDP/6DcPejqAHUreNdpCWYEnbCA7YkPqcPAQ2jiHEqCvaT5+FXXxHObH44Gfy8beT+qp+IAgSsMhHevJSTzviE9Lge/L4IlYfR/zlM3YRQGkP/UYd6cIWC2dK8mIbdhOo8T/tIX8EZMpN65sIyUO9Md6og3LpU+rItRvG2MMWxkHsUmAnbelW+yfDqI8y6Q/Gts8hxC67mwhSTpqq4DtuJ2A3rfX7wrETH+IUu+lvxiZton9y/ue76jgOn/rJjzP1JWXzN8YWnxm3LPLhV+YTfcV8Iw0kP39jbFAm9UQdMHyezhfGPmWGvXwOe4kH2BH20nbKZbyHyMEmbKNfY77FfOA7fEOZOb+4oHa/kC/md4wvSP3BaBNjE9vScYPviZv4hnrxDXOFPNgdPojYAfEVtuLfiI9hG3bTPnxFOaQnP36gTOzFbvwUc570+IX5kB6P+RmM+Rxtpz2UX7UzGPXRZuYntqbt5i+fY42JGIEPcutatJFyxrK3Op53ZqKxpibYDjGGYHttvhLRB11MkAiaITT4S2BhoEfgJX23BirlMPAjqDFBmVAECernb0wS7EvrJ8gx0QgGHGfyhd1MRiYYwTeCIxOZdExQ6iHQkCcWlmr5Vfs4jh/Ih42UTV3Uw1+CALYS3Cif4JTWwzE+Yy/lUW6Qz7FwUjZpw+8EWAJt2JTahb30C+mog0UXW8IHtJ3yKDeCZuq3ydZH2/AneagDX+CHIPXzXYwf6sHv5KVsbMiVj10EScqmLeSNxSLyRZ40L8GVvLEQ0R7yR/DmGOWndU6EYV+MA+rBLuqh32McVNuPb+l/xlf4H1urtkyl/ZMh9cFYyLANG7GVerE9FSKcQHGpsMrYVSZdiB3ajM2MkZhT1f5O7Qi/+q5Ka34xroJ8xhcsnviGv/QzaSH9EeOW8qgz5ivpgqQlL2VRJuOT8vkbY5XysT3iXdpXOXspN+ylDPxHHdiEDdiEbZE++pT/812Mh078wngLWyH1xtzFjmgXaWPOp/ONv3zGrpjDMVdSf0fZUU6IGvKGbdgdsYD2pP6MsRvxLvom5g71Ym8cT+cnpGx8T9vpw5hrOTshx7AVP1XnGf6MdnOM9lAe9VN2jNGom/TkIw/tG8/etN92ZnZHsP2B8Y+Nr7EO+/dWp4gtMvAYzAxCBiODmIHJIGUCpIE3JkGunMmS8ig3ghMTJOrnL/bEJMFO0gfDbvJhJ/aSjwkJowzKZNEjHZOQ8kjP97nyU9uiHuzDDwSvtB6CM38JBJTF8Vw95MGGdGFJy+d7jpOOciDlhN9Tn4Vtqd9y7cemtF7KIhDxd7L1cTzalvZV+CL8wXeUTRrSpvVTVrVsmLOLdlEfPiJvmi8YdsWCQL5qu6OOXP7xGHmr44B6YgGItlfbj/34lfG1pdo/WVJnOh7oJ+rEdhbcEG9xAoQoC/KZ7zlOOhY08uF/2ouf0nGeqx+GDaSlnbQ9/ApTP3IM32Mn/od8X41P0U8xLyIt+WNOUmaM3ZgnfB99RVnt+iqdBzEOohzKrJZDWv4fc4Y86fGcf6r1YHvMt/AL/48xEr6I8mPORTuiTFj1D22nvCDl8h3l4NvUH9Vy0nET/oz82Mxx6iI/5VBetCVspI1RZpSfjsucnRHfqCvKwk/kqfqUsvgubKVd5KHcdJxG+qifY53YK5rGem2htdBcaK/9jGixjgQbiX/feJTxFcbTzPEP5isSfXAyaJlQDHoGMoOTwZpOuC01QGNCUQ/1Uy/1Y0cEDOwjXZovJhZ5mUTkx15IOfwlL8fIT7poa6SHuUlerQeShry5eiDft6sn7IhjUSZM20A6GGVF2nZ2pXlzdvFdtd6p1JfLH/WlbFd3rlyYK5f8ndrFcdJFHvJ3WnenpIxqXam/07ZH+0m3pds/WUZ7qJM6qBP7mXuxQIY4aCdKU7FDPvJj80T8Hm2PdlMGcz8YcSj6lL/h4/BzWh9/q/1DHhjfUWbEubSOTvyd2kueqr3VcsK/fBfjI45TVif1tPNLlBc+ST/n2hFlhj2kTX1R9Qd1j1dO2EaeNH/YEH0TdUZ6/lI+x9OyJ2InTMuq2lkti3Thp+gDjqXpIw92dWrvzky0FZtiTa3VkWCDTzPuZnymcV/j84wvNB5v/NOenoFP5CsTnQzAGNhVxrFcvm5xsvWneSIwVhkBI62D74Lj1QGreaPsCGjj1VM9Xi07LTfypGWl6VNG3jR/ylw5kWey9VXzp8z5I8rNlZeyWm7VrlyeYJo3zd9p3Z2Ssqp2QtodjO/S+juxoVouf7dEG3IMG9P6Y6GMBa7KOBYL31RtTW2oMo7l0sR37cqK/6dM8wfjWFrOWJxIWWna+H96fCymeXNMy6t+hmOVCavlBcfKHxyrjGr++Bzp089pmSnTNNXyU3ZazmTyRL70cy79zsqZd5vGOtX48kJzsVmGBkOLocnQZm0F2zOM+xifazzC+DLjKT09/3Nh2eFinelgrjKXvtvM1RvMpRdFsXtM51uItlSIQsRZ9btUrE11rqY2VDlWmrSMsdKNx1w5YzFXRnC8tNXjY7GatxPmyqkyly9lLk+VuXzBTtJW0+SYy1dlLl/K6cqzsxFt1fNq4x8ZjzSivdBg4wq2XY0Itr2NBxsPN77EeJLxL+xs8Df5CkVRFEVRFMXOOf9xk1pnmL462fhS4wuMzzEi2NBi4wq23Y3PNh5oPMx4nPGVxv/W0/Omm/OViqIoiqIoip3z/H9ybdVzYqG10FwHGdFgaDE0GdosdFoT/AcFt4uRm9z2NMaTovzaQfHgQc9f9fTc+NN8xaIoiqIoiuL4REsd+FbTVfHAAVqLV3rwS1N7GdFiaLInd9cCIdh4GoEtON7/wU1vXEvlmipbdVwW/fOenhde3tMz74n8tWlRFEVRFEWxPdFQp8w3TfUXxrgcygMHaC6eEEWDocXGFWxswXGzG1tybM0933iMkZe6oQT/0sqelTdCFEVRFEVRzBOx9mdrTEv9lZH3r/2J8VgjWgvNxTMEaDC0GJoMfVYSbIAvuFaKouPaKZdF431s6S7bG4yn9/S8ZLCn5/qH8gaJoiiKoiiKLaKZ0E49f238cyO7a7yJg921eP8a2gsNhhaL+9dqSHfZ2IpD4cXTooca4142Hj9lG48nG87r6XnT7f5IuiiKoiiKoljm3CdcK+0zUGin/278UyO/bsAVTB42QGuhudIX5o4r2NKnRbmOiuLjuiqPm/IUA5dGqQjRdrrxHOPbe3pOfU9Pz8Xf6OmZ9WjeYFEURVEUxR2dc/+jp+e6n/f0XP49k0ofNB12temkc43srCHWeFEuWuoPjbzvlh8q4EHP2F2Lp0Nr96+lqO6y8R4Q7mWLJ0a5NEoFIdq4PPpG41nG84wXGy8zXmHEwGuM7yg4UxRFcSfitRNgLr8oitsHQ+egedA+aCC0EJoIbfRmI1qJy6CINe5be7ExLoXyZGjcu5Y+bNCRYIt72eK3RSmI97Kloo3Lo9zTxk1z7LZhzJnGs40oyfONbzNeaLzIiOGiKIqiKIo7EtE4EM1zgREN9BYjmghtxK7a64zcs8ZlUDQUYo3XeMSDBlzRjFd5jLu7BjiY7rLFpdFUtPEQApdHue7KzXIoRYzgCVJ23P6H8S+NbzL2G9kChFy3xXhRFEVRFMUdgWgbiM7hNjG0DxoILYQmYlPrFCM/QMDPT6GduAyKlkJT8asGiLW4FIr2CrE2pmADIdiqoo0CEW1s3XG9lUdQjzJyXxvCDdXYZ8QwtvwQcCjKPzPyJl/4elEURVEUxR2EoW/QOmgetA8aCC30KiO3kCHU2FX7AyM/+ZkTa1wKjQcNxt1dSxHKLrfTxj1tPIjAEw1UinBja4+nSDGI138cb+SSKSIOY9mFgyhMURRFURTFHYGhb9A6aB60DxoILYQmQhuhkRBq3FaGduK5ALQUmirdWZuwWAuEaKOAEG1cX+WmOJ5kQBlSKZWz48arPzCIrT523o42Yijbf5AXw4miKIqiKO5IDJ2D5kH7oIG435/bx9BGbG6hlbhCiXbip6fQUl0Ra4HYZYudNm6Gi6dHUYZUymVSdtwwBIN4BQgCDiXJDXUYG+RdI6IoiqIoijsCU42D5kH7INDQQmgiLn2ikUKooZ3QUGipEGuhs2KjbNKIAigs3W2jMtRhiDd23djiQ8BhGL9FipGQnbiUiDtRFEVRFMXtkVVdE3oH7YMGQguhidBG3KcWO2rx2o7qrtqUxVogJ9qoMIQbl0oxBIMgAg4DMTSIshRFURRFUdyRmGodtA9EB6GH2NQKoRY7altMrKVIhVuIt1TApSIuhFyVGC6KoiiKorg9s6pvQvuEOIOhjVKRlgq1LYqoJBiVVwVclWG0KIqiKIrijsKc5gk9lBNpwWlFtfJgKuJSpg0QRVEURVHcnpnTOsGcPtpukDNeFEVRFEVxe6cgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCNsBenr+P/GJbf3IDe/dAAAAAElFTk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</file>
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MVM8/vX3yp8LWXLDyLRUwc4/n0QZ8Kby9YmI0sj+Z67jNnuXOl5olr0P62VhDHOn76mdI5pY5Td/GO8VuPdA42fR73k0aJRxxfjTqGOiaVosdIx86bK1XHrdLfPz0Wlc6rmCr2O5ZSze+zTB+DYmj/+ufLmwOxN2uNRbAhbu9gW2axNtVi7bu6UjegOdzSMDjc09QW5jYPC0ss1lYMHvHBWnTy6wmVnOTy6KRfKtZEsWCr5sSeR/sqFlN581SyzhSN9eJQX+suXpx4wfb6zTOzzypDQZXOW0wFRzXHIaLHqlxcVXuMRbkA0j4riWwPHUdvzry/K/GcUQ8dB28exN6sNVZtg01XCRDrzZXm+u0QbLqd+m9/c7bFWlPhyppuq/7EYu3OwnPhhoUFLcMLsab9x7Wkt2Z18tTJThGg70Xf1K0f5wqLrkzkfzbPPBqfP0HrY50AtT/9vz7XftI5nrKTsHf1SNv8xk6ycZ362Duhal7Nkc6bN09+jRHtX6GTX2uKt3apMMkfyzw6ocfv5dU23lxpsHnHJT6Gsljkah/e/Hm1hhT93DoOCqe41mK/H8WORzRdWzzGcV6pz/M/o34mb66oF2tah9YY59TaNa/3GOr73rxS26Vof+nvYLoGby7E3qw1Vo2DrcUmRqwzV5rrz6tdsL1poaaratP6NYVL9Jy1/oPC9QNawi0NQ8Kdja3hoaahhVuhS5ot1mzfq3JrkTpp6YT22rXf7/R1T52MUsptVwydrJ8786wu45860MIq+Vp6Aiy2bVTfS2NAkeWNjRZDx8f7GbVOL4Ze+qqFVjI274bksS9EjTOumGmw5dFx8o6f97hpbDour+ZJY1DH0Js/qp8tjSDt2xur45RH+yo1t+bRmFLH9827Osew1qI1eWOl9pcGvvbhjZXp76H2542T+h3U3OWOM2Jv1BqrtsG2Sq92Q6wzV5jdDbZ333yzcCXtxV/OL7yoYMaU08LUfo3hIvMyi7WrBwwKPxzYEn7aMDjcbbE2d9DQML95WFimq2vJOrpreoLTlQpvXNRDJ8V/P/AId3xqGjiVbvsrO2GmlNrO4/1NmwrzeOOl5ksD5a1H5rpjo12DbZ07rpia3+PNu+5xx0e97bxx0XS8wsMbl/qbm3+abbENHUNvXDp/ueNWTu+xWPfV/+2OTdXvVJ5N117vjkvxxiDuDFpjEWyIpYLtdYuxf+7bEM7t1xAutAi71CLsu+YV/QcVvDLnVRZnCrTrBjSH75s3WqjdaqF2e+OQcF9TW5hjsbZAz1tr3hZrK3Nr6InpCblccKTopFrpiVSmgVjsZOqZbqu1e+NkikKjkjBUsOYpdzy2R7CV+rmi+llStBZvrEwjppJjEU239aK31sGW/l6W+w+JvOm2+r3xxqV4YxB3Bq2xahxszTYxYp25wiwVbOdasF3QtzFc1q8pXGthdr3F2A8KtoQfZv7IvNGcoatpAweHWQ1DwuyG1vDzxrYwt2lomD9oWFg8yELN9rUyt+9a6AaHMy6aUrgS5IwrZv6qiT72xhTzNzd1PhEXosAZJ1PWfcWi0hmXqoDMU+54VHv8UtPQKVz5csZ5vv/qpmyrbRSCzRmnnz1PNfuQaSh7+0kfG63t3w+wKEzGVWp6u7LSx0+mV2OLPSZpiOpn8MYh1rvWWLUNtpXNw+1khFhfLjdfPu/C7F/5nXn9hRfC+RZsl/RrDNMt1m6yILtNV80syO7Qc9Iy71Kg6S8XNLaG+80HLNTmNLWFxwqxNtRibVhY2jzMgk3R5q+ju76SrF0nN29cNMUbU8x0X/9pJ3V9rVIVh3lKrTXFG+Op/aR446Lp+HLHL/W3SbDpc2+cp/aVR8fHG5fuQwGWP67lTIPNW+PaAw7vcgtTj++LFlrp2EpM8dZVyhRvH+lxEdUcf8R60RqLYEMsF2x6PtqV/ZvCTyzWFGWKMYXY49Ji7InMX5qKsyctzhaZS8xl2fy1ijSdPNMTWzURJFO8McX8j+QqTE8h2DoHW7Ft0+DqKcX2k/4sEa1Tj723jef/O/ML2Za1w9uPF5lCX9MtWK3D2w6x3rTGqm2wxasHiPWkoqpcsF1lwXazBdt9ja2FK2eKMrkwU4EW1dW0Jc26orZt7hhs1brGTkY6SW59+pkut35K8Z6dXL35oinemGIWO6F3l1JrTfHGeK53HktvXDQdX+74pabHRJ974zy1rzzFtk3H9ZRSa9ySPAcwj0JI33/WQsjbNuo9Bj3F24/Uf8SU+udDx07/HHnbItaL1lg1DjY7USHWm8vMl8+dmv3rvTMKtml9G8I1/ZrCTAu2hyzYnrBg0zbLc3PU2jfuutu9clAJheBw5oymeGOK+duHaxds+vk2XTPd3Y9M8cZ4rnceS29cNB1f7vilpsdEn3vjPLsEW5Ftaxlsiptnz/i8u5+ojkm5ff5u5aqwZv/Dim5fS8odU61DY0r9M6Ofu9TvG2Jv1hqrtsGmExhivbnUfKlEsF1kwXa1BdtPLdgezIJN28Roq7Xv2ImwJ+hE680bTfHGFDONk3L76okp3hhPLxa8cVEv2LxxxUyPiT73xnmmUVRs20rH1VodG/0+FguhGH/edinpmO3hags3/ceOnntXjB117BBrqTUWwYbYm4JNJ5sUnRR1ktFJUCekdJtqgyPFG1PMdH06MXrjamGKN8az2lio9vil6rHJU00QVBpi7z79TDZiG7ot6Y3bXur37j9uutW99ej9DrzwlW9k3/0Q73d3e6o1FPuPn1evme5ug9hbtcaqcbA12cSIdeZS86XvVBBsAyzYGizYGi3YbJtluTlq5R/e7HxCfGfFqm0nOmdsdH2y9kJwOOOiKd6YYqb7Et64WpjijfGsdo3VHr9UN9iccZ5usDnj0n1Uu8Zamq5FFAIoGZei45yO2RG+cPY3ulxxK0SmMxaxt2qNVdtgW9Y01E5iiPXlErN8sDWGWwc0hwcahoTHG1sL2yzNzVELnz/769leP0Sx5o3N+7ITHN64aIo3pphaT4rW7Y3tqSneGM/0eAhvXLTa45e6OQkYfe6N80yDrdi2CqI8ukXpjdtRplf8vHWnkfTGnXd3GbOj9P7Z8sYh9latsWocbI02MWKducQsGWx9LNj6WrD1t2AbaMHWYMFm2yzNzVEL3dBwxqW6weGMi6Z4Y0qZnoh1FdAb11NTvDGe1R7Hao9fqhtszjhPN9iccasndw3lX8+41R27I6zkZ94y/8nsu9vQ1eN0zI40xRuD2Fu1xqptsOkEhlhvLjbXlQi2Cy3YrrJgu8WC7RcWbI9ZsGmbGG210guNDjtRe2Oj+n4aUIoAb2w0xRtTSoVCitbujS2m1v30aZ9zvxdN8cZ4esfRGxftznHP68WLN87TCzZvnFQY59FVtmrWKXXMq93GM42x1++8u8sY7SulmmMT1dUx7+vVqJ85j46dNw6xt2qNVetga7OJEevLxea671yQ/au8M9uCbWAWbIMs2AZbsA0pbLMkN0etTNFJ2hsnX7Y1p895E9uCzd9GpnhjypnuVyfAjVdf547Nq5O4TvYav73WqeOS4o2Ldkw+NBv1IZsfntNl3LbA7Pw1qbF5vG2L2TXYim/rBZBifVvQ+NtEdUxi8BXbhx5TrUdjve9HtT89fnmKrSGNTFHJ8dFjogiMv2femF/PuKWwDs2n8d6YaLqOd596xh2H2Fu1xqptsOkEhlhvLjJfLBFsUy3YrsyC7ecWbI9asGmbGG211DvB6SSqk9dLtkapj9MTfR59z5s7muKNKafW4aETrE6gire4Xn2sr3lXAr25oyneGE9vbd64vOnahNandb9lgRm/325hkG6rMXn0eTqmmOnjWG7bdF+RuNZ4zOVrFjRaexrXxfaRR9to2/zjqPmK/X5680kdrzTuhL6m+TVnfs1am2IqxZs7PRbaLv/PSZwv/fmFvufNidhbtcaqcbA12MSIdeYi88V/LhJsz78QLtxjYLiqjwVbPwu2ARZsAy3YbJvFuTlqZft+/gmuFIqJfHAUTqDO3NEUb0wl6mRb7Vrz6ITtzRtN8cZ4vuQ8lt64vAqTStDc6babH0qCzT5PxxSzS7BVsK2OW0/Qz+rN2x30e6ffWW++6HNf/robTZWifXjzpse9UvR7682H2Ju1xiLYEHtTsMmnTvtcpwArhU7eOmHmT/w7KtikTsZpdJRDJ+9KTpop3hjP7gSb9K4epXjb7ehgk4quaiNI+/KCM1ptgOuKVrlYi2pcJcc3j9ai41FsH+nvfTk0X7FYReztWmP1KNg0WBtpY00yZbGejI1YZy4y15z238PbTz2d/at9G1s2vhqW/Pgn4dI+A8N1fRvDTD2H7YNg27adN1+t3GAnl7ftJJeemHWSUqg9ZWuOY/NXXbRNfp7U/Hz62BtTrb/68tcKJ1etLT3pax/6ur6vcd72nt1d56r9Dum0rfbtjfNU0ChE0n3ra/qet41CJ48+98Z5/uaO2dlW24JCj7k3rpgar8feCxdFv9atfeR/V0qpY6f163conVPr09fS371q1HZaT3qMRX7+ao5D/ncvnTMeg2oeE8TeqDVWt4Otj9k12AbaxIh15iJzoTnHYuze/i2FK2nX9mkIl5vT9hgYrrb/v8GCbVa/5vCQjXlsgAVbbntERMTtqRora61uB9twMwbbyTqJIdabirUnzUctxB60ILujf3O4qe+g8OO+TRZqTWGGeZtF3D0Wc3NtzBOmtvHmQkRErLXWWDUJtr3Mw8yT5g8Y8rtFul2EWGcuNH+pV4BasD0woCXcbdF2p3m7hdps+//7zUfs60/Y9xdk4715EBERa6011slZa6m51F5NplqsomDT4GHmnuah5okP9Wt+aaGuPiDWofYfHIUgm9d/cHi4f0t40HzAfMicY197zNSYBbltEBERt6dqK2usk7LWqijY5J+Yu5l7mI3mUHOCebB5/Iw+jQ94O0OsF580FWRScRaNX9P3ve0QERG3h3f2HbTcGusE85CsuXSxTA2mFl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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:11:1};
b={1:11:1};
c={1:11:1};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b + pow(c,3);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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<text></text>
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<text></text>
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</answers>
  </question>

<!-- question: 361133  -->
  <question type="formulas">
    <name>
      <text>L62 - ab - c2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{a}({b}) - {c}<sup>2</sup></h3>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                  sizeN              size of the font w/o px, e.g. '14'
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{a}({b}) - <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>There are no operations in the parentheses.<br>Move down to Exponents&nbsp;<br>
                <p><span>&nbsp;<span class="" style="color: rgb(255, 51, 102);">{c}<sup>2</sup>= {c} x {c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="Exponents" width="201" height="57"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span> - {=pow(c,2)}</p>
            </td>
            <td></td>
            <td>
                <p><span>Multiply <span class="" style="color: rgb(51, 102, 255);">{a}({b})</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">
                        </span></p><p>{=a*b} - {=pow(c,2)}</p>
                    <p></p>
            </td>
            <td></td>
            <td>
                <p>Add&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=a*b} - {=pow(c,2)}</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>a={5:11:1};
b={5:11:1};
c={1:5};
d={1:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a * b - pow(c,2);</text>
</varsglobal>
<answernumbering><text>abc</text>
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  </question>

<!-- question: 361134  -->
  <question type="formulas">
    <name>
      <text>L62 - d(a+b)2+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">{d}({a} + {b})<sup>2&nbsp;</sup>+ {c}</h3>
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p></p>
                <p>{d}(<span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span>)<sup>2&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(255, 51, 102);">{a} + {b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">{d}({=a+b})</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b}</span><sup><span class="" style="color: rgb(51, 102, 255);">2</span></sup></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);"></span></p>
                <p><span class="" style="color: rgb(152, 202, 62);">{d}({=pow(a+b,2)})</span><sup><span>&nbsp;</span></sup><span>+ {c}</span></p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Multiply:<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><sup><span class="" style="color: rgb(51, 102, 255);"></span></sup></span></span><span class="" style="color: rgb(152, 202, 62);">{d}({=pow(a+b,2)})</span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Multiplication.png?time=1624663720836" alt="Multiplication and Division" width="200" height="55" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{=d*pow(a+b,2)}</span><sup><span class="" style="color: rgb(204, 51, 255);">&nbsp;</span></sup><span class="" style="color: rgb(204, 51, 255);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(204, 51, 255);">{=d*pow(a+b,2)}</span><sup><span class="" style="color: rgb(204, 51, 255);">&nbsp;</span></sup><span class="" color:="" rgb(204,="" 51,="" 255);"="">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
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      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>d={1:11:1};
a={1:7:1};
b={1:7:1};
c={1:8:1};</text>
</varsrandom>
<varsglobal><text>d=4;
a=2;
b=5;
c=4;
ans = d*pow(a+b,2)+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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  </question>

<!-- question: 361127  -->
  <question type="formulas">
    <name>
      <text>L62- (a+b x d)3+c</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Evaluate the Expression:</p>
<h3 style="text-align: left;">({a} + {b} x {d})<sup>3&nbsp;</sup>+ {c}</h3>
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    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td width="25%">
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 51, 51);">{a} + </span>{b} x {d}</span>)<sup>3&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; Multiplication comes first.<br>
                <p><span>Multiply&nbsp;<span class="" style="color: rgb(255, 51, 102);">{b} x {d}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="200" height="55" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p>(<span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{a} + </span><span class="" style="color: rgb(51, 102, 255);">{=b*d}</span></span>)<sup>3&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>Now simplify the addition in the parentheses<br>
                <p><span>Add <span class="" style="color: rgb(51, 102, 255);">{a} + {=d*b}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 102, 255);">({=a+b*d})</span><sup><span class="" style="color: rgb(51, 102, 255);">3</span>&nbsp;</sup>+ {c}</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <p><span>Exponents<span class="" style="color: rgb(51, 102, 255);">&nbsp;</span><span class="" style="color: rgb(255, 51, 102);"><span class="" style="color: rgb(51, 102, 255);">{=a+b*d}</span><sup><span class="" style="color: rgb(51, 102, 255);">3</span></sup><span class="" style="color: rgb(51, 102, 255);">= {=a+b*d} x {=a+b*d} x&nbsp;{=a+b*d}</span></span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,3)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></p><span class="" style="color: rgb(51, 102, 255);"></span>
            </td>
            <td></td>
            <td>
                <p><span>Add&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{=pow(a+b*d,3)}</span><sup><span class="" style="color: rgb(51, 255, 102);">&nbsp;</span></sup><span class="" style="color: rgb(51, 255, 102);">+ {c}</span></span></p>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="201" height="57" role="presentation"></td>
        </tr>

        <tr>
            <td>
                <p>{ans}</p>
            </td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></text>
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</file>
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MVM8/vX3yp8LWXLDyLRUwc4/n0QZ8Kby9YmI0sj+Z67jNnuXOl5olr0P62VhDHOn76mdI5pY5Td/GO8VuPdA42fR73k0aJRxxfjTqGOiaVosdIx86bK1XHrdLfPz0Wlc6rmCr2O5ZSze+zTB+DYmj/+ufLmwOxN2uNRbAhbu9gW2axNtVi7bu6UjegOdzSMDjc09QW5jYPC0ss1lYMHvHBWnTy6wmVnOTy6KRfKtZEsWCr5sSeR/sqFlN581SyzhSN9eJQX+suXpx4wfb6zTOzzypDQZXOW0wFRzXHIaLHqlxcVXuMRbkA0j4riWwPHUdvzry/K/GcUQ8dB28exN6sNVZtg01XCRDrzZXm+u0QbLqd+m9/c7bFWlPhyppuq/7EYu3OwnPhhoUFLcMLsab9x7Wkt2Z18tTJThGg70Xf1K0f5wqLrkzkfzbPPBqfP0HrY50AtT/9vz7XftI5nrKTsHf1SNv8xk6ycZ362Duhal7Nkc6bN09+jRHtX6GTX2uKt3apMMkfyzw6ocfv5dU23lxpsHnHJT6Gsljkah/e/Hm1hhT93DoOCqe41mK/H8WORzRdWzzGcV6pz/M/o34mb66oF2tah9YY59TaNa/3GOr73rxS26Vof+nvYLoGby7E3qw1Vo2DrcUmRqwzV5rrz6tdsL1poaaratP6NYVL9Jy1/oPC9QNawi0NQ8Kdja3hoaahhVuhS5ot1mzfq3JrkTpp6YT22rXf7/R1T52MUsptVwydrJ8786wu45860MIq+Vp6Aiy2bVTfS2NAkeWNjRZDx8f7GbVOL4Ze+qqFVjI274bksS9EjTOumGmw5dFx8o6f97hpbDour+ZJY1DH0Js/qp8tjSDt2xur45RH+yo1t+bRmFLH9827Osew1qI1eWOl9pcGvvbhjZXp76H2542T+h3U3OWOM2Jv1BqrtsG2Sq92Q6wzV5jdDbZ333yzcCXtxV/OL7yoYMaU08LUfo3hIvMyi7WrBwwKPxzYEn7aMDjcbbE2d9DQML95WFimq2vJOrpreoLTlQpvXNRDJ8V/P/AId3xqGjiVbvsrO2GmlNrO4/1NmwrzeOOl5ksD5a1H5rpjo12DbZ07rpia3+PNu+5xx0e97bxx0XS8wsMbl/qbm3+abbENHUNvXDp/ueNWTu+xWPfV/+2OTdXvVJ5N117vjkvxxiDuDFpjEWyIpYLtdYuxf+7bEM7t1xAutAi71CLsu+YV/QcVvDLnVRZnCrTrBjSH75s3WqjdaqF2e+OQcF9TW5hjsbZAz1tr3hZrK3Nr6InpCblccKTopFrpiVSmgVjsZOqZbqu1e+NkikKjkjBUsOYpdzy2R7CV+rmi+llStBZvrEwjppJjEU239aK31sGW/l6W+w+JvOm2+r3xxqV4YxB3Bq2xahxszTYxYp25wiwVbOdasF3QtzFc1q8pXGthdr3F2A8KtoQfZv7IvNGcoatpAweHWQ1DwuyG1vDzxrYwt2lomD9oWFg8yELN9rUyt+9a6AaHMy6aUrgS5IwrZv6qiT72xhTzNzd1PhEXosAZJ1PWfcWi0hmXqoDMU+54VHv8UtPQKVz5csZ5vv/qpmyrbRSCzRmnnz1PNfuQaSh7+0kfG63t3w+wKEzGVWp6u7LSx0+mV2OLPSZpiOpn8MYh1rvWWLUNtpXNw+1khFhfLjdfPu/C7F/5nXn9hRfC+RZsl/RrDNMt1m6yILtNV80syO7Qc9Iy71Kg6S8XNLaG+80HLNTmNLWFxwqxNtRibVhY2jzMgk3R5q+ju76SrF0nN29cNMUbU8x0X/9pJ3V9rVIVh3lKrTXFG+Op/aR446Lp+HLHL/W3SbDpc2+cp/aVR8fHG5fuQwGWP67lTIPNW+PaAw7vcgtTj++LFlrp2EpM8dZVyhRvH+lxEdUcf8R60RqLYEMsF2x6PtqV/ZvCTyzWFGWKMYXY49Ji7InMX5qKsyctzhaZS8xl2fy1ijSdPNMTWzURJFO8McX8j+QqTE8h2DoHW7Ft0+DqKcX2k/4sEa1Tj723jef/O/ML2Za1w9uPF5lCX9MtWK3D2w6x3rTGqm2wxasHiPWkoqpcsF1lwXazBdt9ja2FK2eKMrkwU4EW1dW0Jc26orZt7hhs1brGTkY6SW59+pkut35K8Z6dXL35oinemGIWO6F3l1JrTfHGeK53HktvXDQdX+74pabHRJ974zy1rzzFtk3H9ZRSa9ySPAcwj0JI33/WQsjbNuo9Bj3F24/Uf8SU+udDx07/HHnbItaL1lg1DjY7USHWm8vMl8+dmv3rvTMKtml9G8I1/ZrCTAu2hyzYnrBg0zbLc3PU2jfuutu9clAJheBw5oymeGOK+duHaxds+vk2XTPd3Y9M8cZ4rnceS29cNB1f7vilpsdEn3vjPLsEW5Ftaxlsiptnz/i8u5+ojkm5ff5u5aqwZv/Dim5fS8odU61DY0r9M6Ofu9TvG2Jv1hqrtsGmExhivbnUfKlEsF1kwXa1BdtPLdgezIJN28Roq7Xv2ImwJ+hE680bTfHGFDONk3L76okp3hhPLxa8cVEv2LxxxUyPiT73xnmmUVRs20rH1VodG/0+FguhGH/edinpmO3hags3/ceOnntXjB117BBrqTUWwYbYm4JNJ5sUnRR1ktFJUCekdJtqgyPFG1PMdH06MXrjamGKN8az2lio9vil6rHJU00QVBpi7z79TDZiG7ot6Y3bXur37j9uutW99ej9DrzwlW9k3/0Q73d3e6o1FPuPn1evme5ug9hbtcaqcbA12cSIdeZS86XvVBBsAyzYGizYGi3YbJtluTlq5R/e7HxCfGfFqm0nOmdsdH2y9kJwOOOiKd6YYqb7Et64WpjijfGsdo3VHr9UN9iccZ5usDnj0n1Uu8Zamq5FFAIoGZei45yO2RG+cPY3ulxxK0SmMxaxt2qNVdtgW9Y01E5iiPXlErN8sDWGWwc0hwcahoTHG1sL2yzNzVELnz/769leP0Sx5o3N+7ITHN64aIo3pphaT4rW7Y3tqSneGM/0eAhvXLTa45e6OQkYfe6N80yDrdi2CqI8ukXpjdtRplf8vHWnkfTGnXd3GbOj9P7Z8sYh9latsWocbI02MWKducQsGWx9LNj6WrD1t2AbaMHWYMFm2yzNzVEL3dBwxqW6weGMi6Z4Y0qZnoh1FdAb11NTvDGe1R7Hao9fqhtszjhPN9iccasndw3lX8+41R27I6zkZ94y/8nsu9vQ1eN0zI40xRuD2Fu1xqptsOkEhlhvLjbXlQi2Cy3YrrJgu8WC7RcWbI9ZsGmbGG210guNDjtRe2Oj+n4aUIoAb2w0xRtTSoVCitbujS2m1v30aZ9zvxdN8cZ4esfRGxftznHP68WLN87TCzZvnFQY59FVtmrWKXXMq93GM42x1++8u8sY7SulmmMT1dUx7+vVqJ85j46dNw6xt2qNVetga7OJEevLxea671yQ/au8M9uCbWAWbIMs2AZbsA0pbLMkN0etTNFJ2hsnX7Y1p895E9uCzd9GpnhjypnuVyfAjVdf547Nq5O4TvYav73WqeOS4o2Ldkw+NBv1IZsfntNl3LbA7Pw1qbF5vG2L2TXYim/rBZBifVvQ+NtEdUxi8BXbhx5TrUdjve9HtT89fnmKrSGNTFHJ8dFjogiMv2femF/PuKWwDs2n8d6YaLqOd596xh2H2Fu1xqptsOkEhlhvLjJfLBFsUy3YrsyC7ecWbI9asGmbGG211DvB6SSqk9dLtkapj9MTfR59z5s7muKNKafW4aETrE6gire4Xn2sr3lXAr25oyneGE9vbd64vOnahNandb9lgRm/325hkG6rMXn0eTqmmOnjWG7bdF+RuNZ4zOVrFjRaexrXxfaRR9to2/zjqPmK/X5680kdrzTuhL6m+TVnfs1am2IqxZs7PRbaLv/PSZwv/fmFvufNidhbtcaqcbA12MSIdeYi88V/LhJsz78QLtxjYLiqjwVbPwu2ARZsAy3YbJvFuTlqZft+/gmuFIqJfHAUTqDO3NEUb0wl6mRb7Vrz6ITtzRtN8cZ4vuQ8lt64vAqTStDc6babH0qCzT5PxxSzS7BVsK2OW0/Qz+rN2x30e6ffWW++6HNf/robTZWifXjzpse9UvR7682H2Ju1xiLYEHtTsMmnTvtcpwArhU7eOmHmT/w7KtikTsZpdJRDJ+9KTpop3hjP7gSb9K4epXjb7ehgk4quaiNI+/KCM1ptgOuKVrlYi2pcJcc3j9ai41FsH+nvfTk0X7FYReztWmP1KNg0WBtpY00yZbGejI1YZy4y15z238PbTz2d/at9G1s2vhqW/Pgn4dI+A8N1fRvDTD2H7YNg27adN1+t3GAnl7ftJJeemHWSUqg9ZWuOY/NXXbRNfp7U/Hz62BtTrb/68tcKJ1etLT3pax/6ur6vcd72nt1d56r9Dum0rfbtjfNU0ChE0n3ra/qet41CJ48+98Z5/uaO2dlW24JCj7k3rpgar8feCxdFv9atfeR/V0qpY6f163conVPr09fS371q1HZaT3qMRX7+ao5D/ncvnTMeg2oeE8TeqDVWt4Otj9k12AbaxIh15iJzoTnHYuze/i2FK2nX9mkIl5vT9hgYrrb/v8GCbVa/5vCQjXlsgAVbbntERMTtqRora61uB9twMwbbyTqJIdabirUnzUctxB60ILujf3O4qe+g8OO+TRZqTWGGeZtF3D0Wc3NtzBOmtvHmQkRErLXWWDUJtr3Mw8yT5g8Y8rtFul2EWGcuNH+pV4BasD0woCXcbdF2p3m7hdps+//7zUfs60/Y9xdk4715EBERa6011slZa6m51F5NplqsomDT4GHmnuah5okP9Wt+aaGuPiDWofYfHIUgm9d/cHi4f0t40HzAfMicY197zNSYBbltEBERt6dqK2usk7LWqijY5J+Yu5l7mI3mUHOCebB5/Iw+jQ94O0OsF580FWRScRaNX9P3ve0QERG3h3f2HbTcGusE85CsuXSxTA2mFl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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={1:7:1};
b={1:7:1};
c={1:8:1};
d={1:5:1};</text>
</varsrandom>
<varsglobal><text>ans = pow(a+b*d,3)+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text></text>
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  </question>

<!-- question: 361135  -->
  <question type="formulas">
    <name>
      <text>L62- a D b P c2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Simplify by adding, subtracting, multiplying or dividing, as indicated:
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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                                              e.g. small, medium, xx-large, 150%, 1.25cm, 22px
                                              since it is always transformed into px units
                          sizeN              size of the font w/o px, e.g. '14'
                          family            family of the font, eg. "Times New Roman", Times, serif
                          txt                 text of the input, e.g. '123456'
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    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <p>Simplify:&nbsp;&nbsp;</p>
            </td>
            <td width="25%">
                <p><span class="" style="color: rgb(51, 51, 51);"><span><span class="" style="color: rgb(51, 51, 51);">{a}&nbsp;\( \div \)</span></span></span><span><span class="" style="color: rgb(51, 51, 51);"><span><span class="" style="color: rgb(51, 51, 51);"> </span></span></span><span class="" style="color: rgb(51, 51, 51);"><span><span class="" style="color: rgb(51, 51, 51);">{b}</span></span> + <span class="" style="color: rgb(255, 51, 102);">{c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup></span></span></p>
            </td>
            <td>
                <p>&nbsp; &nbsp; &nbsp;</p>
            </td>
            <td>
                <h3 style="text-align: left;">Exponents:&nbsp;<span class="" style="color: rgb(255, 51, 102);"> {c}</span><sup><span class="" style="color: rgb(255, 51, 102);">2</span></sup>
                    <p></p>
                </h3>
            </td>
            <td>
                <p><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="201" height="57" role="presentation" class="img-fluid atto_image_button_middle"></p>
            </td>
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        <tr>
            <td>
                <p>&nbsp;</p>
            </td>
            <td>
                <p><span class="" style="color: rgb(51, 51, 51);"><u><span class="" style="color: rgb(51, 102, 255);">{a}&nbsp;\( \div \)</span></u></span><span><span class="" style="color: rgb(51, 51, 51);"><u><span class="" style="color: rgb(51, 102, 255);"> </span></u></span><span class="" style="color: rgb(51, 51, 51);"><u><span class="" style="color: rgb(51, 102, 255);">{b}</span></u> + {=c*c}</span></span></p>
            </td>
            <td>
                <p>&nbsp; &nbsp; &nbsp;</p>
            </td>
            <td>
                <h3 style="text-align: left;">divide&nbsp;<span class="" style="color: rgb(51, 102, 255);">{a} \( \div \) {b}</span>
                    <p></p>
                </h3>
            </td>
            <td>
                <p><img src="@@PLUGINFILE@@/ooo-Multiplication.png?time=1624463020172" alt="mult or division" width="200" height="55" role="presentation" class="img-fluid atto_image_button_middle"></p>
            </td>
        </tr>

        <tr>
            <td></td>
            <td>
                <p><span class="" style="color: rgb(51, 255, 102);">&nbsp; {=a/b} + {=c*c}</span></p>
            </td>
            <td></td>
            <td>
                <h3>Now add<span class="" style="color: rgb(51, 255, 102);">&nbsp;</span><span class="" style="color: rgb(51, 255, 102);">{=a/b} + {=c*c}</span></h3>
            </td>
            <td>
                <p></p>
                <h3 style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Parentheses" width="201" height="57" role="presentation">
                    <p></p>
                </h3>
            </td>
        </tr>
        <tr>
            <td></td>
            <td style="text-align: center;">
                <p>{ans}</p>
            </td>
            <td>
                <p><br></p>
            </td>
            <td></td>
        </tr>
    </tbody>
</table><br>
<p></p>]]></text>
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</file>
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MVM8/vX3yp8LWXLDyLRUwc4/n0QZ8Kby9YmI0sj+Z67jNnuXOl5olr0P62VhDHOn76mdI5pY5Td/GO8VuPdA42fR73k0aJRxxfjTqGOiaVosdIx86bK1XHrdLfPz0Wlc6rmCr2O5ZSze+zTB+DYmj/+ufLmwOxN2uNRbAhbu9gW2axNtVi7bu6UjegOdzSMDjc09QW5jYPC0ss1lYMHvHBWnTy6wmVnOTy6KRfKtZEsWCr5sSeR/sqFlN581SyzhSN9eJQX+suXpx4wfb6zTOzzypDQZXOW0wFRzXHIaLHqlxcVXuMRbkA0j4riWwPHUdvzry/K/GcUQ8dB28exN6sNVZtg01XCRDrzZXm+u0QbLqd+m9/c7bFWlPhyppuq/7EYu3OwnPhhoUFLcMLsab9x7Wkt2Z18tTJThGg70Xf1K0f5wqLrkzkfzbPPBqfP0HrY50AtT/9vz7XftI5nrKTsHf1SNv8xk6ycZ362Duhal7Nkc6bN09+jRHtX6GTX2uKt3apMMkfyzw6ocfv5dU23lxpsHnHJT6Gsljkah/e/Hm1hhT93DoOCqe41mK/H8WORzRdWzzGcV6pz/M/o34mb66oF2tah9YY59TaNa/3GOr73rxS26Vof+nvYLoGby7E3qw1Vo2DrcUmRqwzV5rrz6tdsL1poaaratP6NYVL9Jy1/oPC9QNawi0NQ8Kdja3hoaahhVuhS5ot1mzfq3JrkTpp6YT22rXf7/R1T52MUsptVwydrJ8786wu45860MIq+Vp6Aiy2bVTfS2NAkeWNjRZDx8f7GbVOL4Ze+qqFVjI274bksS9EjTOumGmw5dFx8o6f97hpbDour+ZJY1DH0Js/qp8tjSDt2xur45RH+yo1t+bRmFLH9827Osew1qI1eWOl9pcGvvbhjZXp76H2542T+h3U3OWOM2Jv1BqrtsG2Sq92Q6wzV5jdDbZ333yzcCXtxV/OL7yoYMaU08LUfo3hIvMyi7WrBwwKPxzYEn7aMDjcbbE2d9DQML95WFimq2vJOrpreoLTlQpvXNRDJ8V/P/AId3xqGjiVbvsrO2GmlNrO4/1NmwrzeOOl5ksD5a1H5rpjo12DbZ07rpia3+PNu+5xx0e97bxx0XS8wsMbl/qbm3+abbENHUNvXDp/ueNWTu+xWPfV/+2OTdXvVJ5N117vjkvxxiDuDFpjEWyIpYLtdYuxf+7bEM7t1xAutAi71CLsu+YV/QcVvDLnVRZnCrTrBjSH75s3WqjdaqF2e+OQcF9TW5hjsbZAz1tr3hZrK3Nr6InpCblccKTopFrpiVSmgVjsZOqZbqu1e+NkikKjkjBUsOYpdzy2R7CV+rmi+llStBZvrEwjppJjEU239aK31sGW/l6W+w+JvOm2+r3xxqV4YxB3Bq2xahxszTYxYp25wiwVbOdasF3QtzFc1q8pXGthdr3F2A8KtoQfZv7IvNGcoatpAweHWQ1DwuyG1vDzxrYwt2lomD9oWFg8yELN9rUyt+9a6AaHMy6aUrgS5IwrZv6qiT72xhTzNzd1PhEXosAZJ1PWfcWi0hmXqoDMU+54VHv8UtPQKVz5csZ5vv/qpmyrbRSCzRmnnz1PNfuQaSh7+0kfG63t3w+wKEzGVWp6u7LSx0+mV2OLPSZpiOpn8MYh1rvWWLUNtpXNw+1khFhfLjdfPu/C7F/5nXn9hRfC+RZsl/RrDNMt1m6yILtNV80syO7Qc9Iy71Kg6S8XNLaG+80HLNTmNLWFxwqxNtRibVhY2jzMgk3R5q+ju76SrF0nN29cNMUbU8x0X/9pJ3V9rVIVh3lKrTXFG+Op/aR446Lp+HLHL/W3SbDpc2+cp/aVR8fHG5fuQwGWP67lTIPNW+PaAw7vcgtTj++LFlrp2EpM8dZVyhRvH+lxEdUcf8R60RqLYEMsF2x6PtqV/ZvCTyzWFGWKMYXY49Ji7InMX5qKsyctzhaZS8xl2fy1ijSdPNMTWzURJFO8McX8j+QqTE8h2DoHW7Ft0+DqKcX2k/4sEa1Tj723jef/O/ML2Za1w9uPF5lCX9MtWK3D2w6x3rTGqm2wxasHiPWkoqpcsF1lwXazBdt9ja2FK2eKMrkwU4EW1dW0Jc26orZt7hhs1brGTkY6SW59+pkut35K8Z6dXL35oinemGIWO6F3l1JrTfHGeK53HktvXDQdX+74pabHRJ974zy1rzzFtk3H9ZRSa9ySPAcwj0JI33/WQsjbNuo9Bj3F24/Uf8SU+udDx07/HHnbItaL1lg1DjY7USHWm8vMl8+dmv3rvTMKtml9G8I1/ZrCTAu2hyzYnrBg0zbLc3PU2jfuutu9clAJheBw5oymeGOK+duHaxds+vk2XTPd3Y9M8cZ4rnceS29cNB1f7vilpsdEn3vjPLsEW5Ftaxlsiptnz/i8u5+ojkm5ff5u5aqwZv/Dim5fS8odU61DY0r9M6Ofu9TvG2Jv1hqrtsGmExhivbnUfKlEsF1kwXa1BdtPLdgezIJN28Roq7Xv2ImwJ+hE680bTfHGFDONk3L76okp3hhPLxa8cVEv2LxxxUyPiT73xnmmUVRs20rH1VodG/0+FguhGH/edinpmO3hags3/ceOnntXjB117BBrqTUWwYbYm4JNJ5sUnRR1ktFJUCekdJtqgyPFG1PMdH06MXrjamGKN8az2lio9vil6rHJU00QVBpi7z79TDZiG7ot6Y3bXur37j9uutW99ej9DrzwlW9k3/0Q73d3e6o1FPuPn1evme5ug9hbtcaqcbA12cSIdeZS86XvVBBsAyzYGizYGi3YbJtluTlq5R/e7HxCfGfFqm0nOmdsdH2y9kJwOOOiKd6YYqb7Et64WpjijfGsdo3VHr9UN9iccZ5usDnj0n1Uu8Zamq5FFAIoGZei45yO2RG+cPY3ulxxK0SmMxaxt2qNVdtgW9Y01E5iiPXlErN8sDWGWwc0hwcahoTHG1sL2yzNzVELnz/769leP0Sx5o3N+7ITHN64aIo3pphaT4rW7Y3tqSneGM/0eAhvXLTa45e6OQkYfe6N80yDrdi2CqI8ukXpjdtRplf8vHWnkfTGnXd3GbOj9P7Z8sYh9latsWocbI02MWKducQsGWx9LNj6WrD1t2AbaMHWYMFm2yzNzVEL3dBwxqW6weGMi6Z4Y0qZnoh1FdAb11NTvDGe1R7Hao9fqhtszjhPN9iccasndw3lX8+41R27I6zkZ94y/8nsu9vQ1eN0zI40xRuD2Fu1xqptsOkEhlhvLjbXlQi2Cy3YrrJgu8WC7RcWbI9ZsGmbGG210guNDjtRe2Oj+n4aUIoAb2w0xRtTSoVCitbujS2m1v30aZ9zvxdN8cZ4esfRGxftznHP68WLN87TCzZvnFQY59FVtmrWKXXMq93GM42x1++8u8sY7SulmmMT1dUx7+vVqJ85j46dNw6xt2qNVetga7OJEevLxea671yQ/au8M9uCbWAWbIMs2AZbsA0pbLMkN0etTNFJ2hsnX7Y1p895E9uCzd9GpnhjypnuVyfAjVdf547Nq5O4TvYav73WqeOS4o2Ldkw+NBv1IZsfntNl3LbA7Pw1qbF5vG2L2TXYim/rBZBifVvQ+NtEdUxi8BXbhx5TrUdjve9HtT89fnmKrSGNTFHJ8dFjogiMv2femF/PuKWwDs2n8d6YaLqOd596xh2H2Fu1xqptsOkEhlhvLjJfLBFsUy3YrsyC7ecWbI9asGmbGG211DvB6SSqk9dLtkapj9MTfR59z5s7muKNKafW4aETrE6gire4Xn2sr3lXAr25oyneGE9vbd64vOnahNandb9lgRm/325hkG6rMXn0eTqmmOnjWG7bdF+RuNZ4zOVrFjRaexrXxfaRR9to2/zjqPmK/X5680kdrzTuhL6m+TVnfs1am2IqxZs7PRbaLv/PSZwv/fmFvufNidhbtcaqcbA12MSIdeYi88V/LhJsz78QLtxjYLiqjwVbPwu2ARZsAy3YbJvFuTlqZft+/gmuFIqJfHAUTqDO3NEUb0wl6mRb7Vrz6ITtzRtN8cZ4vuQ8lt64vAqTStDc6babH0qCzT5PxxSzS7BVsK2OW0/Qz+rN2x30e6ffWW++6HNf/robTZWifXjzpse9UvR7682H2Ju1xiLYEHtTsMmnTvtcpwArhU7eOmHmT/w7KtikTsZpdJRDJ+9KTpop3hjP7gSb9K4epXjb7ehgk4quaiNI+/KCM1ptgOuKVrlYi2pcJcc3j9ai41FsH+nvfTk0X7FYReztWmP1KNg0WBtpY00yZbGejI1YZy4y15z238PbTz2d/at9G1s2vhqW/Pgn4dI+A8N1fRvDTD2H7YNg27adN1+t3GAnl7ftJJeemHWSUqg9ZWuOY/NXXbRNfp7U/Hz62BtTrb/68tcKJ1etLT3pax/6ur6vcd72nt1d56r9Dum0rfbtjfNU0ChE0n3ra/qet41CJ48+98Z5/uaO2dlW24JCj7k3rpgar8feCxdFv9atfeR/V0qpY6f163conVPr09fS371q1HZaT3qMRX7+ao5D/ncvnTMeg2oeE8TeqDVWt4Otj9k12AbaxIh15iJzoTnHYuze/i2FK2nX9mkIl5vT9hgYrrb/v8GCbVa/5vCQjXlsgAVbbntERMTtqRora61uB9twMwbbyTqJIdabirUnzUctxB60ILujf3O4qe+g8OO+TRZqTWGGeZtF3D0Wc3NtzBOmtvHmQkRErLXWWDUJtr3Mw8yT5g8Y8rtFul2EWGcuNH+pV4BasD0woCXcbdF2p3m7hdps+//7zUfs60/Y9xdk4715EBERa6011slZa6m51F5NplqsomDT4GHmnuah5okP9Wt+aaGuPiDWofYfHIUgm9d/cHi4f0t40HzAfMicY197zNSYBbltEBERt6dqK2usk7LWqijY5J+Yu5l7mI3mUHOCebB5/Iw+jQ94O0OsF580FWRScRaNX9P3ve0QERG3h3f2HbTcGusE85CsuXSxTA2mFlOTqc2KBtvuZoPZZo4zDzSP+6dP9r984YDBtgPE+vXJnAuSz73xiIiI20u1lTXWp82DzPGm2ksNVjbYdjUVbAPNIeYYc3/zGPPMOf2aX3+yv53cEBEREbHbPt6v+d1Ru+zyP6yvjjUPMMearaaCTS1WNtg+aQ4wW8xR5r7mp8xTz9u9/4+8nSIiIiJi5V63+8DZaivzyKy11FyDTTWYWkxNpjaLnVZAH6jgPm7qSW79zPhKUf21g8ILD8wv/LzvoFcW2I4QERERsXrVUiN22eVvrKviCw7UWnpLD/2lqf6mWkxN9sHVtUgMNr0aQZfg9P4fetKb7qXqnqou1em26BmH/umu//Bo3+atC/q1BERERESsXDXUX+22x2XWVGea8XaoXnCg5tIrRNVgarGywaZLcHqymy7J6dLcaHOSqTd1Uwl+fsqun5g633aKiIiIiJU5z2Lta7v2+b611BdMvf+a/l77PqZaS82l1xCowdRiajL1WadgE/qC7pWq6HTvVLdF4/ux5a+ynW5+8aSP73bxvX0GbfQWhIiIiIgfqmZSO1lD/YV5hqmra3onDl1di++/pvZSg6nF4vPXupC/yqZLcSq8+GrRkWZ8LptefqrLeHplw5fP+0S/u+f3bQ6IiIiI2Nl5fQZtVSu17bLL32ft9BnzeFN/3UB3MPViA7WWmiv/hrllgy3/alHdR1Xx6b6qXm6qVzHo1qh2pGj7ovm35jf+dtc9bv7h7gNX/mKPps2/tAUiIiIiftSc02fQe7P7NG66ZfeGp/5+tz4/a91ll3+yTvqSqStrijW9Ua5aaj9T73erP1SgF3rGq2vx1aFdnr+WJ73KpvcB0XPZ4itGdWtUO4jRptujZ5l/ZX7Z/Lr5d+Y/mlrgt83/k/l/EREREXcyY+eoedQ+aiC1kJpIbfQ/TbWSboMq1vS8tclmvBWqV4bG567lX2xQUbDF57LFvy2qifS+bPlo0+1RPadNT5rT1TYt5i/NvzZVkmebXzXPMb9mauGIiIiIO5NqHKnm+YqpBvpfpppIbaSralNMPWdNt0HVUIo1vY1HfKGB7mjGt/Ioe3VN6Jv5q2zx1mg+2vQiBN0e1X1XPVlOpahF6BWkuuL2WfPz5p+Zf27qEqDUfVstHhEREXFnUG0j1Tl6mpjaRw2kFlIT6aLWcab+AIH+/JTaSbdB1VJqKv1VA8VavBWq9oqxVjLYRAy2NNo0oaJNl+50v1UvQd3T1PPaFG6qxqNMLUyX/BRwKspTTL2TrzwNERERcScx9o1aR82j9lEDqYWONvUUMoWarqrtZepPfnqxpluh8YUGZa+u5Yll511p03Pa9EIEvaJBO1W46dKeXkWqBentPw42dctUEafF6iqcVGEiIiIi7gzGvlHrqHnUPmogtZCaSG2kRlKo6Wllaie9LkAtpabKX1mrOtYiMdo0QYw23V/Vk+L0SgaVoXaqneuKm976QwvSpT5dedvb1EJ1+U/qjeEQERERdyZj56h51D5qID3fX08fUxvp4pZaSXco1U7601NqqZrEWiReZYtX2vRkuPjqUZWhdqrbpLripoVoQXoLEAWcSlJPqNNio3qvEURERMSdwXzjqHnUPgo0tZCaSLc+1Ugx1NROaii1VIy12FnxQlm3iRNosvzVNu1MdRjjTVfddIlPAaeF6W+RapFSV+LyKu4QERER69G0a2LvqH3UQGohNZHaSM9Ti1fU4tt2pFfVehxrES/atMMYbrpVqoVoQVIBpwVqoVGVJSIiIuLOZL511D5SHaQe0kWtGGrxitp2i7U8+XCL8ZYPuHzExZBL1cIRERER69m0b2L7xDiTsY3ykZYPte1K3Ek07jwNuNS4aERERMSdRa95Yg95kRbdoaQ7j+YjLm/+B0BERESsZ73WiXp9VDd4i0dERESsdwEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACgDvjYx/4/vt1HHhcNtOEAAAAASUVORK5CYII=</file>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>b={1:11:1};
c={1:10:1};
a={1:5:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[a=a*b;
ans=(a / b) + pow(c,2);
ques=join("",a," \\( \\div \\) ",b," + ",c,"<sup>2</sup>");]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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  <text>0</text>
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  <text></text>
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  <text>ans</text>
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  <text></text>
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  <text>_err == 0</text>
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 <subqtext format="html">
<text><![CDATA[<h3>Simplify:&nbsp; {ques}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361138  -->
  <question type="formulas">
    <name>
      <text>L62- a(b+c+d) +f2 - p(pow(base,p)) + g / h (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{a}({b} + {c} + {d}) + {f}<sup>2</sup> - {squareRoot} + \(\frac{{g}}{{h}}\)</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"></div>
<table>
    <tbody>
        <tr>
            <td width="40%">
                <p></p>
                <p>{a}(<span class="" style="color: rgb(255, 51, 102);">{b} + {c}</span> + {d}) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; <br>{b} + {c} + {d}<br>
                <p><span>Work from left to right.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(255, 51, 102);">{b} + {c} = {=b+c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="100" height="40" role="presentation"><br><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}(<span class="" style="color: rgb(51, 102, 255);">{=b+c}</span><span class="" style="color: rgb(51, 102, 255);">&nbsp;+ {d}</span>) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>
                <p><span>Finish simplifying inside the parentheses.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(51, 102, 255);">{=b+c} + {d} = {=b+c+d}</span></span></p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>{a}(<span>{=b+c+d}</span>) + <span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2</span></sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Next Exponents from left to right<br><span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2 </span></sup><span class="" style="color: rgb(51, 255, 102);">= ({f})({f}) = {=f*f}</span><br></td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}({=b+c+d}) +&nbsp;{=f*f}&nbsp;- <span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Square roots are exponents.<br><span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> = {base}<br>because {base}<sup>{exponent}</sup>&nbsp;={factors} = {=pow(base,exponent)}</td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{a}({=b+c+d})</span> +&nbsp;{=f*f}&nbsp;- {base} + \(\frac{{g}}{{h}}\)<br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.<br><span class="" style="color: rgb(204, 51, 255);">{a}({=b+c+d}) = {=a*(b+c+d)}</span><br></td>
            <td style="text-align: center;"><br><br><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="100" height="40" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span>{=a*(b+c+d)}</span>&nbsp;+&nbsp;{=f*f}&nbsp;- {base} + <span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\)</span><br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.&nbsp;<br>Division can be show with a fraction bar.<br><span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\) = {=g/h}</span><br>
            </td>
            <td style="text-align: center;"><br><br><br></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 102, 51);">{=a*(b+c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f}</span>&nbsp;- {base} +&nbsp;<span>{=g/h}</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right.<br><span class="" style="color: rgb(255, 102, 51);">{=a*(b+c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f} =&nbsp;</span><span class="" style="color: rgb(255, 102, 51);">{=a*(b+c+d) + (f*f)}</span><br></td>
            <td><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(51, 204, 255);">{=(a*(b+c+d))+(f*f)}</span><span class="" style="color: rgb(51, 204, 255);">&nbsp;- {base}</span> +&nbsp;<span>{=g/h}</span>

            </td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(51, 204, 255);">{=(a*(b+c+d))+(f*f)} - {base} = {=(a*(b+c+d))+(f*f) -base}</span></td>
            <td><br></td>
        </tr>

        <tr>
            <td><span class="" style="color: rgb(70, 255, 150);">{=(a*(b+c+d))+(f*f)-base} + {=g/h}&nbsp;</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(70, 255, 150);">{=(a*(b+c+d))+(f*f)-base} + {=g/h} = {=(a*(b+c+d))+(f*f)-base + g/h}</span><br></td>
            <td><br></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={-3,-2,-1,2,3,4};
b={-10:-1,2:10};
c={-10:-1,2:10};
d={-10:-1,2:10};
f={2:12:1};
g={-5:-1,1:5};
h={-5:-1,1:5};
pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};
</text>
</varsrandom>
<varsglobal><text><![CDATA[g=g*h;
base=pair[0];
exponent=pair[1];
squareRoot=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}
ans=a*(b+c+d) +pow(f,2) - base + g / h;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 361137  -->
  <question type="formulas">
    <name>
      <text>L62- a(b-c+d) +f2 - p(pow(base,p)) + g / h</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{a}({b} - {c} + {d}) + {f}<sup>2</sup> - {squareRoot} + \(\frac{{g}}{{h}}\)</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"></div>
<table>
    <tbody>
        <tr>
            <td width="40%">
                <p></p>
                <p>{a}(<span class="" style="color: rgb(255, 51, 102);">{b} - {c}</span> + {d}) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; <br>{b} - {c} + {d}<br>
                <p><span>Work from left to right.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(255, 51, 102);">{b} - {c} = {=b-c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="100" height="40" role="presentation"><br><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}(<span class="" style="color: rgb(51, 102, 255);">{=b-c}</span><span class="" style="color: rgb(51, 102, 255);">&nbsp;+ {d}</span>) + {f}<sup>2</sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>
                <p><span>Finish simplifying inside the parentheses.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(51, 102, 255);">{=b-c} + {d} = {=b-c+d}</span></span></p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>{a}(<span>{=b-c+d}</span>) + <span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2</span></sup>&nbsp;- {squareRoot} + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Next Exponents from left to right<br><span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2 </span></sup><span class="" style="color: rgb(51, 255, 102);">= ({f})({f}) = {=f*f}</span><br></td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}({=b-c+d}) +&nbsp;{=f*f}&nbsp;- <span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> + \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Square roots are exponents.<br><span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> = {base}<br>because {base}<sup>{exponent}</sup>&nbsp;={factors} = {=pow(base,exponent)}</td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d})</span> +&nbsp;{=f*f}&nbsp;- {base} + \(\frac{{g}}{{h}}\)<br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.<br><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d}) = {=a*(b-c+d)}</span><br></td>
            <td style="text-align: center;"><br><br><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="100" height="40" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span>{=a*(b-c+d)}</span>&nbsp;+&nbsp;{=f*f}&nbsp;- {base} + <span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\)</span><br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.&nbsp;<br>Division can be show with a fraction bar.<br><span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\) = {=g/h}</span><br>
            </td>
            <td style="text-align: center;"><br><br><br></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f}</span>&nbsp;- {base} +&nbsp;<span>{=g/h}</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right.<br><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f} =&nbsp;</span><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d) + (f*f)}</span><br></td>
            <td><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)}</span><span class="" style="color: rgb(51, 204, 255);">&nbsp;- {base}</span> +&nbsp;<span>{=g/h}</span>

            </td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)} - {base} = {=(a*(b-c+d))+(f*f) -base}</span></td>
            <td><br></td>
        </tr>

        <tr>
            <td><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} + {=g/h}&nbsp;</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} + {=g/h} = {=(a*(b-c+d))+(f*f)-base + g/h}</span><br></td>
            <td><br></td>
        </tr>
    </tbody>
</table><br>]]></text>
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</file>
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j2sfT9CLLBDy8GP9ykxYVFhgWHeCmX9X2Awf5l2IeWZdk/5qN/LjL2mjtVWOXwIP7O2M6tccVubq1pEmbN5OYQV2spR5FD15y6h7vwsZtDrY2Y/+zDbrUTtnKrn7eTW/OaSW4tCcfKdmqxyvfh9/IxI8WyHSNlS9pebD93nHGJKY3VuuJvzdv2cy1BBd+acz4VpnE9Fkn8rXzYJ9yEozZ1R8z+Ufi0Hjz4MeHozdyqp23jVrt0olvjukluzZn7ujVnfyrf3gB88q8vhJr74Ns4YmM3QclsleO2CJ/WY5HE38qHfNytcuwWblWJv9Uv28Wt0bu3W/NW2ZJpZ7h55OOXBssKPPn68271q3bzXOP6SX224f9M+SVmGE/v/0j+XtrtNMlKP0zZ3a0xbU+3xi1aXIiX1L4W60NLsuwj7x/z0T8Vw/hXgXzpc/MZyodX7OrnWy1WcvWlJI5m6TjlqDVu2sutfs0e7pW//znUXI83/u/vbsIxyrtnqp3LlXeV37JrQCvN62U1f2K7DW2XjjMOidJYrSv+Vr/tU64lqMBbfc6+YRrXA/E3/vBPuJWP3tRNOKmjcvLvcO6X3YQTO9wq5+3gVr16N7faLXu71Wftm2+vH35xwRmhxnqcd/e1brzE38pHbuImnLBl+LQe3tZDPuZWPnZzN+H0bdyql010q/Uqad26T7atYaV8+u3HLwmWFXjytefcKufu4Lnq5bLt+j3cajfLPu//Uvkl5MwX53vxDG/9/X1utZv2LEg7M+WH2YMfkyEx54dXgx/O39Gt2rOrt2/1GYqX4IdTnrq+1of5f3rC/evsg4s+xLGkD0vJX8sd1W/myCOv/87755E/P+2+MP/Uwj/T9+qbdyM9zsZlQ+aBxroKRe7ezE04Q/nwil3catMmDX7+cKxyBznk/CduCTU34qS5F/s1ws/rKTq5Y07HNUB1tMS87s+OEZg/pzyptt9I2p6jtm8sfLAa/iJH44Ph9sM/AaWxWlf8rXLbvq4lKOG3ypx9whSuB4JqnBLIShJ/40/pcFOfuD18U4+fLrzPrfT9zd34M7dxK1+2s5tw0yS3yq1759urouyY/+oTocY+cFY57tCPuZW+vbFb6ZjN3PjTtgrf1MPbKvG30rE65vStCzt69xy8HUuD6ssRJdGz6E+L3fiTtvRc+dzt3YQpuxZ+ku/9GOTqGQTPf2ZmaKkP5z9xc9HOtD3chJvli5nyxVJoq2nm/PCK/HByhxt/6lZu5Qt3dBOu272wTcfuNP/ocFQf7vvj427CVPWB46bLX/RhtnyWa+/NTvnolf97PXimwCv/++dijK/ZzU24Uf6ZsZdbZdY/qX/+2chc1lyoQi13n6F8eMVEnwf83BlsDiCelEcnXL+7e6Pi3j+/BnRt4caftW3RVpJ7d5rf+G7WZTGvK+0Ygfmz0/0VbV+1i5twrXxA27eo7SUZH2MDpbFaV/xN0AC3BHWWM6EigXhBddgn3DglkJV+uJV7/5QDwzf14MEPf4zO/MZfsKNbmQmtsxlfd67NDP/lzv90b2Qe9Pjpovlu3Dc+5sYdtYlb6Qef9MklB28rx0kgriTxN/7Snd3K0/d0E3RGlWtvWKl+H/5YWfQ8K4G8hef4HytB9uziVr5hkpugRFPzkx8LUWeAE0i2EPuVGIvjxHJbodyMF+eHlvow4+l73PhztnfjL58YxkT+oI7Y3nBTbR3+aMkPL8sPWiRWOkFCWCJ45am7FeMkm8rHgkWvSiyet4Mbf/FObuUpOpY+4Jdce8sL8T/jyTgzvpA+8XcaD2Xquxz8GDPviCktIhO0iIzYGBuXHUMcVaGWuzkZJgdwEthffFWR4zWXmacPv/p0qL0ez736Bzfuu8q9WifGX6S5egMnnEUclnMhWBbzOm/HcyMyfw4vnQSDRa+p7R9vJ3+pbYlAPz74gDHK1GFsntJYrSv+xs/Zx7UENanHz947hGM9EFRjD/u4G3v0Jm7cqVu5lS7e0T30ylPh23qce8+1buxxm7txEjYrKZBX0uQfP2vvov5cuyVOef6OUFM9tjv3y27soR9zYyXqsGHc+duHb+qBrWO+8e/FcafL1kt3cuN1RjleZ3K59oaV6vNhj10cLCuA6Bn73U09x+lMfKXLd3YrTdu9zkf3JTufr/zjdbfD3UcWfbh5Tzf+VvVDIjDrT32W89/VD892Y0/4pBt3znZLNCZDpuLqsEczfvie/ECsdCtWrpZdN8ouHfu5X50WjurDQ39Y5MadvKUbd6Z8pjH1fcAfI9WHpczPLTi97iRnxu/vK8YY3hLGmTHKlGX8yydIfmf8RI3xqR1u3AU7uJWu2a2oS/5cXn1kbJKMr2KlCrXcLfGXyzeDImUUn1Oe+VmovRFjdYLu881527uVro1xqJhvkXn9uV9X2DHc8wcfPJhp+8Un3djvKw9qfMZdqLan7lrkAPJ8rh5j05TGal3xN04GtgQVmOP6EX+jlUDGKIGMOW0rN1aT9IQHrw7f1mPRHyW+vhOOu2QnN1aTf5wWsnFKNtl2S0TslEGdtO9t+MEWbqzEAjbk4G2V+Bsj8TdG4o/jxmkSj5P4y7U3rJRPv5kRf2Mk/Dwl/sYqGY9VMvb+YQxUbtEb9Q+7HHr/eW7sFTpOSWGcBNI4JQbGKh6ftvfeO77iFv3l+VBS7b2y2G3Uva8bc/wn3dizt3Njeya6cUqwaXvDTtn6zYz4GyPxN0biz4+nxJ/vG/3SWP30jwvCkc69/Lc/u89c/z035qQtC58prsbhMy0SI9aHpcxvli+D//k5N/bKiQWZMzFmc/3TonDu0zNqAvCN//d3d85917sxWnDH/LDDjdXiNfYaxQp15OLE+OYi49uP+KvlbomLXL4ZNJXPv/nwRaH2Rnzm6qNae15r/tTZ8fdgx3DPH+pRfT996cHQcvDBTcd4f/n1iranqG1yvOzM1mNsmtJYrSv+xs7Z27UEFZRjZ+8VQrIeUfyN9glkKzfmsp3cmJ6d3cv/m3/wY5tzD3ajT9jCjTl3OzfmKi1mN09yY2fumW834QlP5l8iffycC93oI9T+kRu70acoUVy4vW8/hyj+Rh8jYYGtl+7oxk7fw42dMXD7S53y6aGP1SdJRM/o727iOeYM2Xe5BPK03dzYWXsVY6Byi/7aJ97AoXef7cb8eBs35uId3Jipu7ixN6k/yfFpe/7zG3b3/hnTvY0b/YPNa+RvPuf7bPnhouLq0EczfpD4G32cRDp2Xa04uVF26Vg/Vr2Tij6cs60b/cMt3ehjN3OjdWbux1R+8D4jrkaqD0uTsvnQx0v+eHWxG3P2tgU1v8Zep/7JB94f5T7O1GfqOz4bc77mwmkd3o+jj9+imB98do3ihLjPlTe+ucj4aj5XYfRhH+vL3Zl8M2gSf5qjVThk+ql+bo/50db1+aZV5vWymj/UQ32ql/pph/Z8u+RB2eHbJhf6NVPH5uoxNk1prNYVf6Pn7OVaggrK0bPzE3qhBNUoJZAVj97YrXh6h1vx8h3d6KkT3c0v3BuOqMdPnrjPrXjspm7FM3TsZTr2pt3d6BmT8u1Gqv2HXn861NCHl994zY3q/Khb8Vsfdyses4lb8UdbuRWv3MmN1uTJwdv6DR3Psdh66Q5u9PQm2h8Oqk+HlMTfQomeFSX8PPEPvpy2qxs9a89iDFSuLP4O+elZbsWTtnArnr1N0XeOl5hmvMrt+c/o77W7+L6vKGFVI77Q5/57jgvtDTvV1iEl8ef98D354DjFSffWbrQS3ugbdyvsom+MF31Q/Kx43rbFuJ+jPkj4j75652U3pkuDubj402K34imfLHj+dm70FPmDeZPERY18dqv6fr3iQPGw4gXbFf5hjOUrPht9g3x58x5F2ZEaZ+OyIeOrmKhCQ+4u5ZtBM8RfFc6++xq34neS9ohTX0ZshXm9rOZPrIt6qZ+28QHt0r7s8G1jF/ZhZ64eY9OUxmpd8TdKBrYEFZSjtPDmgKBaQQlkBSWQUZrQozShR0l8bX33t8MR9eDBD45dQYJllBayUZrso3p3D20kbSbc+t6jQul69D56p1tBYm4FJZMVjt/cjTp3W7U90Y1SAsvB28rxEn/eVgmeUUooo5RQcu0OK9XXb2TE3woSfnCUxJ/3pfoyShM9+mZhSfx9Y/YZxfE6Mxx1ifqDP5UcfJlMm76v9JnjenbqI39HX1SMw7BQcfWNjPhbQeJvBYm/URJ/oyT+Rkn8cazvlwSgt/U62axFwfvpKv3USccoJU7fB47JtdfqrIoLnTDBUVoIRmkRGDVN/UziIi3vP+/do4gdCUXvH8YYX/GZFhgfIyM5zsZlwxAPVWjI3aV8M2gyRzX3Fv/tj6GFevQ+codb4chPuBVO3bLIv9epPebqrDBnl/W8Xpbzh/qol/pph/Zol/axg8+wayjjY6xRGqt1xV/bnD1dS1ATum12/mwOQdV22L+7tqM/4dpO39K1Xb6Da7t2omu7eXe38PXnwlH16L7nGtemhb3tx1u5tqt2cm037OraNPl9O5n2577cdx9Eio5zDnJth3zUtUnMtZ36Sdd28fZFXTftFo6oh7f1Gx8pjsdWJZ+26bu5thl7NLar/nqbbtV3fA/5fSZ2Vtta+ErkOI6P5fnb91H0x01ynY9dGCwrwCLf9t2NC0r8eV9ev0tRNtS3MLlnD3TOOt21fUe+P2UL13b+toU/6ZP8X2dz9C9/8x1+klCukb/5nO/r+hPKUkdDfcl3fM73t0DVw89c+2ndof7ORzN++J58QIxI/LUpCbbdKPtiexBb+UwLRdsUfU/MTdPv9J02OabcViR2DGR3tD3anbUd6vvKuiLD53W+EMt18bmO6Xz4guCJAnVxcZri9hLF+VT1ubc0zpSPpE18QfxwLGOMrzQ3asem7Zc5YL/CZ2m/KJPzU8pynbFs9Ev6Xa3N8Hs8luPK/lvaTPtfZ0t/Y0q5Uj1l9tf/yPhduY1m/FtmiKsqNORu5lDsS66+gRjaK+epCMRf27c/7tp+qHxNHDNv6RttwoHmdTyWn/gmMn4+kN18H2z09UVfp3VDfD/Y+RPrpZ5Yby1mwt9pW7nxjHbRDu3RLu1jB/ZQvr84KPcvtlmzoyp2xVx9kb5eHRP7Fpn6LO13rc3we11bob5cOyNJE39NMAx8DlnxR9BqwLsX5f/dz8I/qgyCJS5kTHCCg8DItJ97vcuCFxa6tsPV7uEfc23Hb1aIhCt31IKo4BZzaFb89b54XyjhfNtdv5laHAcJZoK4YrLMe/U3oWRRdvL9JxflorDyZXWsyjcj/nqfnxe+HRx6nvlJkUQRCNhM22rz5eQdcJyde9EH8VtpDLqfmRGOdO7lf7xe9IPjguDo/t0Mt+D1p+vGh+MWvPZb1/X4lCKBcXzSfsOkxw+DEX9i2ccddxxRfB/HMiaYtJ1ae0W/qGPx3+t3J1iwep75qeu4U/XFMauqT39PfvCHruf5n3kflHdkAf7FF91P3lz4IhcHqqv9roOzMT4QKBNPdtJ603EDfiyifxiL/vwjtt95cG1sGc8UtImfel+4102en8Q2fkqTe6bedNzwly8b4qnjF0e63j/c1+DHOCbtc75Y6b+lzY77jvLjii3lcYnx3RAnce70Y1M693p/f2+t/+23H+Tm/ek3db6m37U5xHED5J1KYo/sqsIyEX/fUs4+JZysR/EnDjSvO+49sm488Ff7baW4GMD2zscvqqtj3p8eb8hTDXYwzgPNH/3d9eQ1lXll7ou/bmq+ZNtmjtfFQNJuiU3H7l3fqvfbAPVmYzeUn/yrHzb0m7Z97ntKuS/6rskxGjG2tPgLi90yJ4M1a48wrPWoiT/EHAnkMsSfJvQMDbQGvRyAEX7X7gSJtnO0uPdItN2s4CAwSm2XF7KIrtkXFO0eqbNIdr0u3LY4Q6JdBVkO3tZOiT+ExWnhzPMmBSZnQ7FN9XXhG/WJq/fZe1zbFeoX4pK+IahoJ7Ezsrx4dc4/p/DJFHY4lVjpp3zZNnOPvOghEcdkrHJVu6cDYeFri4v+4VsSLP2UzWV42yC+i77w4z2pTgQDvziovs4HzlUiyT/Qk2Lhn59zHbMOlXhT36+XDSQA/Bbq9z6TLxr9oHFCAB8rkc7uMOVJIMFvDT6ed3YxPhzH4kUbOq5ubNRe16Jr6hbY/uDHnPG+JghPxo06RZJ8OcEPBB6A6rxXdl4VxoM68bVivnwSMBj4vl+mcWaXJNiJiErR+0yIX9rGP7Sb8U/7HQer7L2VczYHP8azNcbET9yhyfq/cdy83fJx7+JfhE+qwYuDux7sKXa2o/9y7Swp1X/ERbr4NoO5L/zKtd94YBEnzG9yg19MG/ufgnlN/yffdXzlS5EXvqZjLi181Hat6p8eYibOnWbIsbKlCm3f/Gh97maeYvtg2khJOca6Svw9/DPXdoTE38mlnH3r7gPPa/W9HJvdj08P8a9j0vxaYX95fOe99FhRvpajdm20g3lbNX/UDieBzeaDBX96yrXfkMRLzCvB3uz6QQxEHxBfmf51zFsKsYst5fwcmMLHrvzRPu2zbsGrvw2fVmPxX19yk+84vn4t8nE8hDhbGjTx1wR9MAxS/JEAFaic8eQwd+F9xeJ+hsoQ3HExLLWbm1Q86OFFHGeQx0gknNlRTE4mL+2qnhyaFn+lCdj71M9dW7dECEKVdpiEPskktgY2TN67f+zafiT7LtquSFD0k8kuNiP+5r38ePh2cJj7u/uLOs7dphBtTDrZXIYXV5AxYNxYvJmUsq9B/Om4niduC381B1410tHbWfgt1p8kO9oalPjT+Db4+GdnFWPjfaxExtgQB8m4VN060B/m/f7RIkbiwqLE2P7TL4Vvlww+HvA1dhJ7OlEhcS8p2i/ct4ivi9V3FlL5CQGXwscv/rlAiy2+zJy8IPwGK2gjGOPJc7saT47S+aExL49b+yX7ucV/eSn81Ry6HriiWKzpa3oykfRlScgCPhjRm4I+tF/z6SAgyA2yifgr9T8FJ2eTZx7rfVeFhX9SPjhTc/hsjR19Tudns33muFLbKYZL/FX5svuuqX3ij/mK8GAMxf7ntXyrvs97pT4f4nsf/wjJmCeq7NdnZbu65l9elGduIE7U/wY77gh2ZObPksSNb5P5Sl0hr3ibVV/T60fSv6USu5xURXFZ9p9+T+Fjd85x/cZuGX4duPHrRRwz5uQ+P0eKfi8TmvhrggSCBimHrPiLCUSiquPn3wpH1oMHP3yZEzd3bedLoNQSW1+7k3/9w3B0PXp+eatE3Idd21EfLy75nquJGXeuCCZNphyaE3+Ni1TvwruKZEUZkgxCKtqaThKxYfL+5EdFHxGPqUAVmxF/7Td/znUuON913n+O67ynu2Gx7Hlghuu84RTXOf2HrvOW01znzNNd55wzXPu5exf31cSFgwmniV2G7xc8T2OQJk+xvIM07/lHwm99WPDHJ13vk3d7Hy14cVH4tB5+EaP/+JtxSsWH2hmy+FN//T2f0cfskMT6NT5cBslh8esvert7n7jLzf3tfLf4zy+Gb/rQdZ8SNfdSsjDIhvL9eOzaRB903nZGjT0Pz3ILX3k2HNWHl/+mExcW9LhYhZ0ELgl1/vo8v8vQ8/iccHSBxa/+oRhj2KtxvlXjPOt0N/mm7xa73pxAUR+CUotJg/gjfvHPWVpEOBEoxXx/wo+xwz+RuT4BXiQ9edZxxaIW7EgXtdy4USYFC8S8Fx5xvYvudnOfvt/7qgzKIBprQp+4GMoiovioWjxpa8FLi2p9r4oRsPh1LaJX7l+9uOn3FLw/Lu0/v8e+z3vuEf83vvbjS7xEoRRzXCnvVJLjNAZVGC7xV4XOG08pTtrL4k/xOOC81lh3PTYlfNuHjiu+2ncCRH3Edoy7xC527FP4uYh/T1J+Jk+GE9QGOzSfq+ZPed4wrpx4d96uPCD7YTmWGeMiH8pe8mFystr0+hH6xxqZjV3NJfJxc7H7omvvSWI3PakKTJHGbcTLf3/NzX3mgRC/D2eP8etAKtSXZCd7abKlxV/i/GVKf09GP+LvmxJ/RymBcA8fCQQhR4ByX4POghe/kV9Y/IMfLPBnKbDZNWAh9IFdtFu1jd1+vIKGBz0QcUxKkghn3P6sRWUVUDnUiT/Kcc8Jiwdn6rGvar88AXsfu7Mo8/14D5oCl/swmIDB1siGycsDGYi5aCeTnYCXb5oRf8VCqrbwjwQar/1IgSBo+7qEMGPAJXBEE/fKIYpPUmJDPNFP6tGkLsPf/wjZPSWxcb9mGLuyiEix4A+LiqRLW5THP2q746Ivu8WvNSaZ7vuvLyY+AjAdK7XV+UhG/B2t+qiX2IgPBeFv+a7BxzefWoyNH1P5mGPDmOZ21Uh2k6cdXcSsp/zGAqg2O2ec5neWI0icXkQjAPGhYpRky6WPrl9eWdyb2aW2iWN8j838Do/bxHXf2/h+yq47Li7mSi0JyhfEPicVsp8djxQ+brlXFXKPK7bSDn1mYaDf8WEf+ZZ7clL0Pq745VgWXNr0Z/gh5jUG3NtXBgKk/TR9T1vEFX4Ksdl+qubmsw+FI/vA4uL9EYWZF/kaM9rRz/K4pfA2yl++X/gRajxy7fQsmFnMD8baL57FfIpzcDBs/9nB2VsBeh6eXcQg/U/iA1bFOIu8j1d2drlRP7VLP6tAXdRZm0ehHfzsY4txYwc/nQelvFPJMMeq4MVfLnc3W3+ZKtff7nhN/CG6auJP7clX/c5rjg1zpPwO2Z5f3eraTtA8INddoTzJfIqiIrGrvJ7MfWp+n8+JJ8ZN8dRgh3JC4/zZrWFzAuHXfrZOumMOh9Qd8gG5gNwy+XrlHvrPWoK9rEHB3qbXD41RZew+NKtoN85bH7tiP/m5LnbjRoyPs4JVQOT5fIYfk/htP3WPrNicfIP6TqzRF38JOLaTjNVIsbXFn5zSCvSD04+g8glEgcbOmL88oQC9lQAt2L2oNxxdD//gB+V+qIlQO2tTMKhM+x35BDLvdwuK9g4Tf6AJ6Se8kpY/i1BZ7NXPHArxJ6H0vTCZaPNGTWR/CTf0NXPvSe9jd2jiqAyL04+1uHHvBzsb8on3TSwrZidv7COJY6oSOHbqzKrz0cxTnTFpnB58yfGcaeIb9ZMt9xTs+LUdIlFAG/iDdjhD5UyRHdFL1cerZS9njLnLvvQLsnvkx47kr37Jvirx50U7NuIP2jxRQvOUIEJO3cK1n79Pw5mfFwbc43m27GIXbZra4ewSPzxS9gPiT/VzSZ++pP6W7xp83CsfYItfUORjjg1jyg3dKbCr/UxNfJ+k1Mb3Vc7br7LEb7A/7mKyg9d2svqGL7Gb2CbWGBfO3OkPPo9k3NipQehiu/zKjk6KuU/eV4jzH7HgqA58wYKC3epr5y+6w5EF/Dwh5iFjhR+xlVj0l6MkDK4MC7fiuUH8cfKCf9jh4FhiAWEm/5RjEPidQo7HP8fKT4wxZeUb3y5UX3M7wV7k03/mVvQVcyQzboDx8ONH/DLeiJ00njQu7Bik8PGBD+j/5YrZ8hweBHMx3jlbc5Z+xxhnrIiB2Hex/bx9/ElEGR1X6YQIu5hLjKs/yVFbFTkJMdB+onwU+x99HeOROGKMqY/7/sgFPh/X96OSHKf5XIXK3N1s/WWqXC6mInyu+rbEH3Ml5nzyQDPzGn8qdsu3Ei1+7Q/FPKYP1Bn9ntqlPpV3yLzgJg/QBnPVz6GM+LtFIrQ8fxTXvS+W5lmcN9+RP+PxxDBjyJwgx5IfmEe0xxUvcpvfSSzsHcz6kY1ddinJEV50iscrnvAfbfq2FbvKb9nYvVKxy7rBnCIOQjtVaz9XJDrO+1LR37q5q7Zkb/sFjeuAP8njOOZI3MkMbdSN10iwpcVfnOTLmpwJViSQhS8qER8aEgiBzpkDSYoBhSrXPus//OWxHDrOPkgJTwETt7WZCErkPc/lL9X5nS6EHwmEM7HyfRjYmxE5wIs/dsmYHOzmkChYcGOChqqjPAF7H5X4iwHORPbiReVIkv4suY8Nk3emzhpTW7lvg4VKZ2+Nokfij7M0SCILZ6LePs4ONVHKD4D4s2Muu5NsmNzxHj92CvELY0EfWYQzfmloL46d7CuLCNB999RiB4qzd3ZnWIQ5a2b86F9g+dIl6Ljg4L4kFv0gNvgBsRPFX9nfOr58M7kXwBzLAk37Pjnvlt2B6J5/XXHPEfFKgqQMJxBc9iYesI2krOTc8+js4vK5Fxo6xotx+YcY5Sd/cyzfcdmIOjijxY+MAfGs37sfuSm0XsD3L4q4eMsC/eNsW7bzQE0Kfzz+hogDfEI/qZ/FA1+GBYlYaRB/xC/+oT1s9Gf2OlbxuuDP9bt+/tIMvomkPeKK8cU39A8/0W/1uXxpdsHvF4bkruOJwZjcZVd53Lj1Y/IV3yriiTGJ8cRCiT/DWHTdf0Uo0Qc/diyu2IGAYExKc3FA6viyIPA7vfiZvhOD0Z547xl9h/Jjx7T/CaX60PPgzKIMxzMuzL0Qt2XU9Z82YwzjO+ZxjCXGmRiJuWow/eRY+b8Klbl7sL6MVF97nvtpqL0eL//11eKKDTtS/lUv6p8/4c/HR3Zea57wBGwZXsiltwDF2wGCXV0Lp4YjC/iT0ZjDiHHijfFS/Q05/OZgRzp/FG8Nt1cgbIgZ/MmxjCN2kwvIFfiXmMZGPieOaDOsedg5mPWjIXZ/o9ilfeYS8wMbEJzYTLv4m5hSPR3Xfy2U6oPfQWVOxRPdsGYwpmUguNuPkZ8ZT966QXtchaA9yjMv1ebcxQ+EEgV8LmP807WbNoi5GEMjRRN/TZBJlAkA0K/4I+lRVkFUvlE3Yu4T9xaBUztrK4RKbjvbP+jxPxJvBBuTlkDzlyrDAhMneybRguVS/JEcOR4b5ZeFfymJPy5JMNlJfCQbLqtShkRJ30gslA1tljEY8Td30X2F7xGbXjipT7SJH1mg6Ftg+3WfCaX60HX7RYWdqdCXbcMj/nZ1XYvqEz5nod5ukj6XYrCfpM+ZLm2waGA/CYlkTV0kMvpI0kRoUTf+xB78zGdRbPM7dXA5g5iE+jsr5ugfgp26Y72MkXzS+eD54cgCtYQJSc4k8xj32MFCh3CkvNi0+FPsluHFcbooInzoexxf+ke/8dGVO7iehY0PAPm+kQsoRxnskn3lceN+1WIXX/GEfewYEBssUuzCUFa+ab/hs6FEH3wbiEyOxxYvsjQHS/Oxkjout0PVcelX+oQYixmXwrw9YWxj/8O4L3j5yVCygN+VpCy5iRhiPgVxU0Zf/8XYf+KRcjEeaYvxinmKunL9qSL+0HyuwnCIP15bk8OC557oa6+Wb9Q32lPfmprX7PIqdsu3Es19cn4xp8kXxCrH+n4U/ipfAfCXRhln5iB+RxzhZ82lZsVf99O3hCMKcDmVy50+NjnJRQAxTxnDSGKasSVm+Z35y/zAVtnZ7PpRvvcYdFwoAUzbkDzB3Ih5i3K0T0zRtny/4OWnQskCPs9weZvYJeaxjbySiZ/JVx9Z3EKFD8mpMXZZC5L+8YR+Ct9GXK+wj3lOLhpsXC8Nmvhrgj6pLqH4o7yClRvac/APfsQzpXDWlrupF/Q8oDMTxBuLILuFBFst8dNesFft5bBcir+SkG5IkLX6NdlJNvgjLhLRvjB+uUk8GPHn/cBkh4xXXKhC0vT9itRn5QTt3/FFgqat6HtN/OESf+Uz8wW/X1TEWmo/yTnY4X0W7eczkiVt00cSKAsV/YzHkRgRsF58ifidz4P/PPVZ50MZMUc8xRMYFit8GMoNGBdxxyS2VRtjUX83Jf4QmRnx4/2OwI87ySwesd+0l/SLOjpu/2Yo2Qc/HiR3/BuTu45tGDfu/zpCbUVRy/yPCzd+jT5W22X4S3Gp/yiTmY+V1HHl+Cj8LFtYnBC+XJpjTkR7Yt8hdilGun8zPZTug4+vuCvJfAz9KMPnTXxdjkdiPfY/tufHGWb60h9DTFRhqYs/lc09gAB67rul78SRe4yJjSjSFE9Nzevgl56nfxKOKuA3BuhHzOuIHPynunNXANrPmFT4Pe6kM8f9PJYdzYg/Hds+96CGviIAJ1/7nSIu8Sd2ECsxN/CTvyP5LBnXZteP8hz3DwcRS+QI5i6xy7xgPGPbxBE/oXzZ/UTj7Vi1KxL0kxyDTzLx423iEj75gpMkYpdciW+S/vIQWxn+hAcbo49ibinH0nCzpcWfD4oWIJNzRoWgevF3SiAKgiMVDJzt+IVJARrvF6A8v/c2nq1FdP/8GiUEBRG7DJfrjCTz7iBEYvv3FVjcs+fFm9ryZ2sK0JuULGNbUIGXQ038EbCUj/eRsDjFsrI1K/5ILNHGWtJK+hjYkMBuDZO3thhogsSJ0bDIyz7a8cm47EuxmfoRKfJ1zf/RPsrrszIq25N9WRHBOOM/FouL5T/6w9l4bDNSC2P5EvW83z1UjF20lbFT2Yb/aBHFUc7faie7SLCgUC/35Pjk3Hj5xt/7Rl+pO8YP9jP+JJ/gI08+QwDSLj7hZ+xnPI4y/M2CRAyKk+efVDyd/eB5xdO7vzpXC9XcYEEB3z/8iB1edCOw5IvQdlNxwb0/tE+ZJP74Oztu+If7fxBYtKW+lC/P+UthtIEgi2fm7IrWxHFoj/7HvquuMjpvkqiLyR1bKU88lMeN4/ADtp0R/BDvcY3xRDtquwy/IKf+Y6HytiW+6I86tnzJ29+LSf/9ZakQoyxojG0c98hgV+cv63d1gV+EERX+vib5j/Lydxl+EWTuMieiqGdxT/sf/Z3O5cGQMqqjCgPm7kGy64n63fYUHWd8vogtYgPfkKvIv/RPgqGpeY0vZV/7jM+Fo/rgd6O8iA47SmHcyjt0PKzmfU6/qZs50aPjiXEdnxV/mfmDHb3P5d9RiRjrXnBDIUQZU8owDygX2vHrQMnXzeZ3XqCcwj+8wg5y9Nd5spN28S9t+HbCTyg7On+diV3mVDo+5D0dX4b3XSriWEujX2JeEstXMYAvh5gml8U1GH8kcTQiNPHXBH3iGYL4C8my53f1Z2sRXpRRXgmXd8LlMO/pBUU7BE6XAo4zG87WmFDlwHlTir9B1k+ZxC5fXp+VUdme7MuKCHzHhPeX25LkXfIDY9L7Qv1/J6mJOhZG7omiLZUfMfEXx5HEw8MW/Yyj/5vP8UUYr3QcYPtPDvILCyKi2ZdHA98/xiznd3FJ4qJGfdas+GvYPYiiFHIZh/kRd6rxRdoOpG0tsOX/4+p3eGkvXk7DxxrnhnFD/BFPMR4QfiweaZ/4XX0qwy/IMedgZxTDOTtzVJ2V8YEwYEEr3/herkOfcT9zGb5f3GzPziljFRb9MnwuI865fI1g6W8+LSkr/BextMVf2acRPBzQ9j8fKtpCoBGHtBXHW3OsqXmNMOZ4+bS8SeDfHcuDH/GkA1/q+LLI77732iLuYG0nPcSPOBjxR3zwsuQq8MqVuc//sngROico2MR6E2O15OcB83sQf+Xbf/z9hoi/KMY4IcqtjZGyvf22L4TSffB99fEvvxD/9FW2luHnCUKeBzy8eJZd9AufJO2Ur3oAH/fkdk6wYn5I1+CRoom/JkiAKlBzaE78FeXbZ34+lGrE5Cu/7ZPg3GfrbxCNmHzZEUXQMBH8ZYAodBoDzsSfji/7hPL6rIzK9mRfVkSQGFisztFilVusIylfJf5I0IjHcGY6LOJPia9hHBEl1BvPbGuLbcZ+yOe06f0P42fFTe1Vl7cGgo9DEmfO7+KIiD/5p1L84aNmd9Q0dxoWIvxMnKTjIT83jBsiieP8ZaZgF7s1af20q/bL8IsUcR9F6mDFn46tjA+EGyeX6c5UVf8zos73q7yzIX+X4Rdr+s8ua1kM5dpaElb4L2Jpir9y3KbovnNKcsuN2iov+oMRfxyvn+W3SPhLv/EyMblQ8VRec97gvl/mEXaQBxjnmF/odyYuKsUfcYHAUh7r/PmPG55KL2PeHx517dfxQmXFVayD9QtfB38PmN+rxB9XNdIdZ4Qbc4k5EcanjvRV9ZTh+1o3/xUPmfXUHxNvb+hnLR5Q/FHWxF9G/Pmk0wJkQG9pDBTgxV/t8X0NJpcCfSIOgZDWceNEN+/lx0LJerCz137q7g2PhgP/KD9njYeHZMkZdQxM3w4TKGlLgZSDX3Sph8DlVRIXEnhhwYllVV92USBB0vaZaptLOX5HoNRHseGBDCbvt8IZEgvcVUo0BLomSufDpXvB/CKvdiAJMuPLpuunTGKXL6/PyqhsT/blRYR8QII5V+LNL1aauGk7kaqj9/cZ8UdbJOizJOq41CI/Zu+Jiwm67O/pXD4s+YDFFrvwwfkhOU/buTFBxsWdnWN2WqYqYd1QYX8V5cfyzeODhY9DEqBfdEtzRlySuKjR+72JcZMgqRR/R8tHzLHLNceu1bGZOK9R41He+fNPhFPHCWrPizrVoXnW1LilcxFWxK1fpIh7v3ugeTwlLj5iWr6KOrYyPjg5OVsLKHUSH1V9F9vnNO78dXR/sYjdk9UvL1qKeCyjuEw3QP+Hygr/RTSVu5tg++1fqNz99rfsHKu+ITSP09yPrzjCt+Qq6tDPQcUH5VS+/BaJrp9eVIyfv2y5g+teWC8QeQGxP/GiXuKT+RDzQPBVg/jjlTPl+UPe43js0dh6saWc0jn3DDdv8UPZdQzwMuSO6V8v5hb10G7i7wYflPM7OTOTA/3ryFgfEaicmCNodZyvO4xRHTVPcjt/Hed/KZxUKR78zr98o3rK8Pn52wPPv6z4Iw6+q/LDGffN0MRfEyQwNag5NC3+oIKIe6FyIEHwnzty8P8SCNFGGz8IC3fctSm34dsx8dcw6Smvz8qobG8piL/yWaz3I235nZVhFn8ZsdH7yM+GLP56Fje+xoKE3rvoLv9+uPazJhWLD6Qdkc9T+Dhk4W9l8Zde9snEeY2ZhcE/yLFcir9SfETxlysfWL24qV9xZ+PNLv50bH8nRP5BD+7VZmcqXvINIsa3RR2DFX+U0+/z/li/mcBLwb3vwwYB/0s3xeTrv1PEDbt+fmc2jE9Sb9Pij+OJOcriN+YL8a65wyuieHI+919qeMee33FEXJGviTFytupr8EFO/Km9htiN4o85h/gr+7dMzZNyngE+FsgBJv6WsfhjArYC2TpWEOVQJ/5qAaOJQCBQLq2HAL9xl4Y3tPcHf9Z4nIIjPuhBGyRUf9akgEnrj7ypH/H3tSD+0sTM9nssK7vLr6WpE39190I09jE7eTnTJNBj0uPShXzRsMjHxdeLAhJToy+brt9PxMQ2yuuzMirbk31ZEYEPSILxsm88Yy5Tdbz8j9Kb+Hm1BW35nT8lP2yVH/sVf2V/ZxKfXyQ4Nl4+5FKlxrU8jguef6Kot3bZWQkrnkA0yfLuBi869k8OElMk6Wg3ffQCcNO8+Iu3MJTnjLgkcVGjPmtq3K6f6Lp+0/hUvbcp7vxxTy2+zMR5ZMddmXeu/fiLhT/Se7s0Hk2NWzoXYUXc+gWZuE8vO5FfsDUtX0UdW35ZsB+XQcZH91M3h9IF/KVH8iH9ipfqiF2J3zJ8DAzU/6Gywn8R/h2DzeTuHEPdVa/xAv5ev//+t75L3PEeO9pJx0s5a1DxEdouP3DDjpvvz0mb+R22FP7fuVEfccNcqN03HsQX9arOhkuvxBrlcnkPO+gDdrGRwGVZ+sfJA32V7b2/uTPU1Ieuuy4p5hiXv/1apvpU14D5nR09tTX3D/X3GfocgY/TnT8EFWOJnWXK5u7fZmIX38V4iA/EqZ4y/Dwh3w0w/3j4rQw/P/zJ4TDGfTM08dcEQ4DnMCjxR2AoQKqekMph3m8XFMKPswWSMhOWSwYkZUROWn/kEMVfefGc94zOJll46xbFfB8bJq9/D18yeZdj8eff84cP4uIYd1/L4yzmRIFP5uniSnn5f1jEn8RNzzP1Dxj51wrR13hPF74iYWfsr5HvaFc+mfxA4+uK/E4fdRJT7A6QfNlR4KZrLj2pn513Zf5dG2NGufTBCvwujpT467i7cYy65l5U+D7eW8ixuXYCe57NvHIj7nxpAa6JnxYUf91P1i9+oP1kfYdw5/UfLKDkh37io/zUpd95ov/UwVj5e9uKeCxjuRZ/+r7j50c0XPJPwXybfMkRRc6lDeKPeY9A8vMuaWdJxB/lNT7lzYSu2y/0u7flF80jwvz93swj8j+x6fOl6qTP1KufgxJ/0RZiD9uIF3zI1Qr8yfFnbun/R3QK/4CG90caZxkfVIi/8uVs0P4Dtc+udU7Ulql+LvhzKXZZ5xindP7Tl8x6auJvydGk+MORLUA/SRvVPyjEn8QZW8A+gSgQ/BawBtMHQqkefd7x08Z3g1XBvx6A+n2gKVjYJu5RYLPtThtp/ZGZMxVQiD+dhX6Hya+6LlBd1ym4/f0boaz6Wb5XzS9oR6p9yp2mSXGpJjWXDEt9LJ9Jgc5bWKSU5OP9JdhOspnOK076W+TzvmxMDqfW139lqL/sm+D7Mirbk31lP4Duefw/ZsQTl23VFv6Tz8pjXd4NeIMzchZFRJK/cZokqramVYk/2cSlAS/+lIS4dEg7N/HgQG6RIJmo3vNUL8Jci8vk+SeGI/rg/zVdrt6S/bDriSl+gfOXTxiv3CUMYuKbIZnRLy5TcxnkMtXNJR2x84FzwtEFfP+YLzm/i0sSFzXqs/K4FeJP9nHLhF+8Cr/Tp/LCWbON+UE/rlYf6D8+StsRi/u86sv716Uwzghh8kGcYxqPpsYtnYuwIm4L8ae4JyfQRj92Zqk6O+48PNTWh5qvTtc8ZwyxqSI+cicDXT+ReCYe/NO+LKDKFfg6d9mX4wbq/1BZ4b+Itm+E3JqOd8hPPr5S8pnmH37rb7cvovuOKUX9h6mf3OvHnCN2mXP0M/Wp2hx0fFBefi3vgvl/Aar4K/8Ls44Lwr8ii+Oby+P6vVH8BTvS+ePFXyiT2hP9xPfEPf5UHPU+/fNQWwEfZ+S4UzVHLu6bz5X5/UT5oJbfNQaZNdTfthDjjkv4CGwd22CnOPmBk0KpPnTdJtHM3K+Lf9ml/pThbY9rcj/zr3NB5j1/rOde/A1j3DfDlhZ/BFMrkLMiBWYOXvzVEogC2SeQImCKM8gS+UwTdsGr9fdi5ODr/uq/FosJweKFlwKSyVdVPxxI/BG4UUiSiPyWeyirfuYW+a65YWJE0cgZI+VCoiw/2RrhF6m67fggzsSs6OHMK56JZ3xZTg5+seVeDxITO01MWL8rSplIlaUOsYzK9lQ+J/5A9y8koPzCruM5E2VxY/KGNibf35hY/I5I7XJY8D2TXmWzfkDoMOZ+pzUswvRF7WQXiZhM4j05JD4du/iNl8JRBRDyfneHccQGxiOOI/WHPsTFrff5XxSJWWf7vLOvDF+X3+lRvxBmMUHjR8VW+y0HNrzf0vePs/l4wpT6XczFX/vJGsO6EyD5HZ/XxpnYLcY5K/7wT3ovG/7h2MWNu/DdP59aHEs8Md/YlcBHwT7fntrNCQB/wzg7WnGxj4tQlfgrj1s6F/18LPpURk38sSOCPxDa0Rdp+SrSDx1ffhclJymTr/524Wd2WtjBYT7ha+/ngjzoUd71ql02K89H+lQl/gbq/1BZ4b8If1XF76AmcYUNIbboJ/HY9fjV/jJ5fzt9Kbzw+y/lWuYG+Za1gV2eON/wf2onY7Ek8aG/y0LIj+HUI8NfBYp/56Z+Up+/gqSTV2wh//sxDfXJrqz4K88fcl7wrY87GOdj/J24oX4dz+teUvh/pVZbTzT//b3aGR/MSE7u4/pB3ZqTDbHLTus1RxXHYid1MnexEdJP/Wy/rSJ2iUfGirmb+kdlyvD5OY2bivmXu8ffiz9/W8gwxn0zNPHXBAlyDWoOgxZ/UMHb9ejVoYZqdP/s6uJ+EeqOixHJiYBOJ2yZCsIcmhN/omwvP0VGQvFJABHHxCKpa0HjLLicLFJ0TlcZFsOlJP7K9ylhl9/uJ6HxFN0l2/oXoLbP+nzRDmUjM35ZEvEH5v52vmu/5FPhJvEgJuiTzvRyr0DpOO+gQvwhkhDx7AAEUTFs4k/2dD/R+B8YeHp88g1H1/zlYyAIZmxJE2Pvs/cUfWSXULFXhr9UQtKMC0oilqirvDMG6sRfec6IJOcyvICjjL/8oz5KlHTccXjfgkPZkNwHI/7abz4w+3+3uSzVfv7exRzBNvpEOyKX9MuXO4G/6Zw+sVgR71zS4pI980v+bSnxF+ot78oCFtHu+67t26lK4gmWYyTC20SuwgfkF8QO+Ypy6lcZrSD+ljbwXdfM8/tu1WEXiTEiFhDS9DE3TvpsieKDuhRbi/9af5LHHE/hT1jjAzZxbPwOuOoLudVTvmpK/CkemNsci8DxYpAYwT5sgqqLn5PvO7Fhjk2ecmRf/CZx0pT4833WSXPmZJT1wL/HkLxJbmPuYlPIE5Wxy3/MSccLfyd5ogwTf0uO5sQfQdkK5Fp+RQLx4q929qiFzJ/FKGgIBMrl6vPBO7HfBz/8/VlflVCLT+f6ezSYsAoUJmxV3fDGClsRf4hJAjcmAAIvJgBIvbKv6r5EziB5srP3tz93C15p3L1c/Jf6JOSffET8xftFSIDc3yBmRU8UY/Q348uuxxpFM77if1v2LrzLLfjjkz7R8OJRn1CYwPQxJKYyKtuTfVW7mREkGtrrffoe1/vMPQ27bBE14QLxQ9wR4f1Osql8X0jND4w7N0373V71gWSq4xsSZHy6NApsjo2LtX5f+Of64yO4LNT71N2u93f3yF+/zNrf85s5/p4dvwskO+a9+Gj4pg/EFf/Qn9c8dN59lut56vaGs/IUPg5ZiOIJU+r3wNx/w8Ev3Lc095n7a3HG/731Zf0Yy5+K5fK4+QeW8E/pXkvvz2t3dl0L6v//ZoQf35cW+UtWjC+7hFX98jsrjK8X7eyCSuAjalkUiHfZ1dS4pXMxmY9leKHFDlu6eNIOfUrLV5F6OVZ+q3pJLw8IzHvhER8f9H/u739VGeP+PyxgDyeW3O+HcPT3TIVxVb/KqF3R6K//Q2WF/4YDrAX+Nh1yLH0jFrivK+4gc+8n/Qu5rI4auyWKD3yrnJD7N3sp2o/Xccw5drUQRtyPhz2IjlJ9DeKPE/jy/FHZFKxl7O51PXil65x/tuu8/xx/4ll+Ghk05Pnk3sOs+COuog/i+oEfNIfLO4oRtdhl7uoEtt/Y5epRFHP00Z/0BP/QTiZ+vO0cP8D8y4o/Nou4Z3A4474Ztrb4w5EtQAZ0emPyAn3iTwGKoOKSqD8L0GD6QMiQ73QmQkBWYe7j84pdOs4SmLDcS8WZTLxHL1dvpL7PYeFLspXEFHf+/P0Gmsh+Cz+UDX3l86rJUoWeR2c3PNnZecPJxRm+v1+Es18lQewXOx+qnxhFUtCEql0OyPhStlb9m7wUC19bXJTHZ5wtht25Mirbk31lETF34b3+fYyDQXG5N8QHfveXi0kWJLHgh9J9ITU/lO+xZFxuyFw+rC0S+JhkUvTV+0zx0n7TZxtEeTNAHLZ371mc8Z8hO2R3+9TJ2Z2y/kDb6f1HXvyxOHrxV/K7H+uJruuRq8LR/YOXy3qRxc4k/b52p37En+YROzDcn3O95hH+IfZVrvuRG8PRgwevovGXpekTY+Z36SWYiXV/z9Agxi2di3E+yidl+N0YL/60gDCPYzzRVlq+P1I3fpA/eAHvksIvnowl89zvnLCoyc+MKfmKdtT/MvrEXz/9Hyor/Lc0wRO9XbPZ7dOJOn1irrPDT44lDpi/xBx9Y4xydurzocRHe++BoVQj/H+HIgd5EaW6/I60YpO6mG9pffq7wY6a+Evmj+J6ScBJUvuJaof8Rj6M9/BSZ67tOvGXrB+KJ0/l9iHF7lOKXe7JJH6xh3zEfPK3O4Tx0pwqw9vvdy77n3+dD2b+hZwXf2prOOO+GZr4a4JMsEwAgCUSf6G+jp8cGmppRMepn3NtX1cySQMMEUOAlSdsmTomhwbxx05iWfxB7NOi0D79s27By0+G0tXgLKtzzul+0eMfcafwly6YvHHb3p+5yX4xK/44A4O1y7AlX2rCT/7FCQMKEHYn/c3EJCuSS3g4o4zK9mRfo4j4mU+ivQ/9LHxSDXaNen4d7mthDL+n5IkP/OWfIApoR8yKP8YovfGYBEFiyYkIfMyx8TJCmkz4qbbar5ns5j57fyjRP7C99wn571gtYCR8hPuPwsmHbOmYfUjTYnLu7+537Wfv6f/XZ0Rt54+HiE5RHKZ+j2OtscrtGpThFw/O1InlIPIbxo2dV/zjL1vJ/1PUFuIY/xCL/K7FcPJtxw34XwpS+DF+cGYRP4xXTOjYQ58YhyjCBztukZSVT8qoXfaN83hJxB9kAeWyvwRK1/zLsu9lq4Kf99yQzzjSdwQCuQrBE28noH7akW1l+EV3oP4PlcF/gz1hGQgv//VV/yaGzutPKk7SWQPSe8bIPfSJuetvqyAOQmzn7JR/ljg+oNoov9Mvwl+GjrbFk8+rKtYS/d1gR3zgI50/yin8h5HB+JX/Kdx+2u5FTvTvDVR9pZOkhrbTB/pK64e3HZ/Ix0scu/gEexDrtIE9Md/GNmRXGb4cgnGA+ZcVf/GkZzjjvhm2kPijYQzAEAyaWAvsZU221kUe0kiDnZtE/b/tQdxwiY4JH89ifOCU6knJd5qw7P69/Pe+y7/+EuYT9xaXe71oUFDGp5eaqRfeUPwnkTpblaz8fx7gDJA6WTS53OYv+5KYGuvwSUtJvPPOH/k3w9PfCOxc8MLC4ulRJg/b4FoEJ089yi+K/hj99DePM0n8bkCYvNQt8jRqamPxj+VVT0xSLKAI6bTPlL1uZ/9vgrj0nIoKgHBisW8/ZTclLPWTMzkEF2ff6mt6qd3f5FvVntrJij8mrnzYcc5B3t7yvTW03/PLGcVllrgLgDjgzJV77IgPJjuigD6prfI9Mf6VMtiE/fGeP8qQiDRW6X+J8T7ukY/9KyFCMknuVfF9YXxJThrvjmv+y186xU7GMAJfxPGsPVwBiRVs534+7KAe6lc/uu67rCEuAHXjm44LD675l78j/NOIR6junN/pI37BfrXDzh6XXtM2iGVs9QKIRYlLNeyMM0dUT/nfXhVPOKsfcfFiHsXLvmEM4iJCrHTefoa/jEk/ymC8uc/R18nYMveh3xlR/YwX8wohSh+oO8TtoMYtMtiXPiCGLzrOP6hx8WFu+MUqKT8QsY9y+ATBphjl5bzsWJdjG/ixVXzWLjtD/EA/YoxTD/VRb9L/9P5PFl9/AjBQ/4fK4L+uh3v6vc2mP3CyAsnL3XdNcZMvP6KY2wgq+k/+i3HIZUx8wJiwu0afmH9+bEq2pdT3SxQfkfp88s+Pr1tLgD/R4oQfOxE4nJik+aRsk3yVPshUy+Hl+UN5ripcd4DrXjDN5wF2wFNQls98LuBBKOI1rhXUxVUNhCj9CvfUznu51Pa1R+XXD+IK2/EH5cmrxO79TcYuMUv8YU+8/y7m5+hn6vesv0Wrtm5QdoD51z7zc3Vxv/DlZ/t2yIcz7pthi4i/VcTWFX+QIEAokdS5h4OzFhI+AUQgpJdmGczcxCqTpECdBByTkglBoMfAZOHlngJusu3RhEOMDVQnJAiZTNxngq0EGQKEYKV+2qE9Fkvq5PhyHUwu7GNR5jgWfwKdnSD6HUlSIKn4HSK1wzG8I4mfLAa0xXcsinGRj5MX4iuEGROPYyP5G/v5Pk70aBflo10cRzs84s8k9jaJ/M0Y0S6Tk6TBJSjKVbanz2N7aiN7+ZAkig/pMwkp9pHxZ7zwB+1D/uY7fIH/GGfGkYkefU6c0B4Jlf4wLnG3jfpJtsQccYIPKEf5IFS8eIpnrZwk4ONU0Mf6Y+ziC9rAJnzkbQ72Yjt/Ux/9wXZOEqLt2MgZOrFFXbSF32gbmykbSR3Uz+fUg5/oD7/7z/XT7yiW/B7HmX4yXiygJH1iKvq4Ns76PfoXX+AT6vFiV7ZiHz6hHDb6Ex71n4Wr5p/AuIgwf5lvLEzEM2XTMU39BKOfGAf6EoUf/qYPcTEY7LhFYht+wTbmQ4xb/EfbcR4zNqn/mmWsnzzA3GCc2f3AV3Gs0n5Hpv1nHBkfcg3lqYf6yuO5JP0fKmmfMYjiHv/hO3I2i3A4matmOCaSvBwFH3GIf4jtOE+IL2I23lfqY6BkU45D9Q/l8TlzifFj3WCORJHCOFEnYoPxYW7l7MJX1MUx/c0f2krnWcwDMWYi6UMkf/M9trFWpnmZNmkfH1A/7dAeddJ+9AF2cSyxxfH8jp+xw8du8B1zlzaJ0fKchdGeOHYxdqknjpv3R2DMn4wNNhHz5LaG+RfKRVIPvgonVr7vtN/suA4n0VgtJP7eKUbxt3OxTd4iZFAJUra8L1JgchnMB6eCgEtX/p4oRJoC5FoFL8f7QOiHXBLhnpsrNeEJduo8SUHBIkm9p6n+bgXMJQqQqWp3mo7N1VPmjaqXY9naj8mcHTDqhn7iyVbapX2OL9fh7dfnsc8klXMV+PSTOri81aXgZxJg6w+Z0PoOsUJfuD+DdvmMHVH+vkx1UBftQepHTGAHl7Xpb6S/zK3P+Z7joi9rdunzq5P+0QZ2YA924UPGJfoPX9BX2m+mPdmX3fkjkZJM8AHtMmZMYtrCJ7F9bMHn+JqE6wWO2vZJt9QffMH4eqEjP9EX6sR3F8qX9NOXC8cytj06Fj+fpfppO/oeH+MbYisdS/6mDvyAP2iHNrAxtbs8nviFOrEB/1EPNhDjfMY7us6WH6gLn1A21kO9J+sz+oOfOA57OTaycpz1O23hFy4LcVy0l7qjvfzN58Qzc496KIevsRuf0BfilvFiHLA99U/aXoxH/M7xxIYX+aG9yOin2Dfa935Su9FPsS9wScbN2wUTu6IfsCvOK+IGP6X+GwwpE+3Db9RHf+hXeV5F4g/8gh34iT4xTpSnHupbGv0fKr3/ROom9hlX5iRt+zhK+tQfY8zhi5hb6LuPa9lPn4gt+sdYMNfoC/3O2VXmUP1Deb6LOZ/yzMcYu9ga68nFf2SMhYHmTxzjGJfYHOMlN1/wG/ZQD3WSN7CVuqgnxgp28Rnt0B7H0360HbvS4/346m/mnM+hOoZ1mP5TjjbLscvffI6tMXbjHKKe8jzid8aTfEf8YFNu/qV2RfIZdcYcho/IWdEPwxX3zbAFxd+/iJuJO8lpfy0GtwWIqkedE5icARC8nLkw+PxkwsVFjMGOZwH9kWMYdMqwcHF2QIAgFiBnBZwJlheUgVhVb6wb2wnGuAMSgzZXD9/7wGdiqQz9pA4CF2HFmRC/s1jwHcGMf7CbdvkM/zCZazsCtBnqp26faHQ8kzCStvic7zkuZxdjEftHGW9TsItxob98F0WBL1PRHn+n7cl/WfHH/U2cuTHxKUcyYJxoK9c+/acv+I+6vb9LfcEf2MUx+A9/+bpVNt4PwxmxP14/GVvGju8YS9rBDnxcFSv8TdvU5dtRWcrU7JbNJELsT2M62o591AGxGXvwPwkcm6mrLi5Efucz+oKdHMdP7zORz6vGOfolxgfH5fzs54nqifHM8djobVM5fEJscgxtEws5/8T2+I56OI6ylMMftIl/Ivmbz2PfaB87o5+oq1w/nw923GLZ1A+0CRkjfErZ6D9YLt8Mo32xnWgj7QzUf+YYcz71f9mOWP+S9H+opO00X9A2vqMPMMZrluGYSOIt2k09jAdzIPbdz+9M/wfiUP0Ty8ecT3lsjWPHODVbD/YTx/3Nn5jH+B2bWfv4Po2X1I98hj1xjcBnPq+pvG8ztI9dfBb7QLu0jx3l9SO1GXti7GILMckY02bMFcRtHFM+T2OXcrXxS+qOJN9hL2ODTZRN51/OLkh/qDPOXfpP282O63CSDbZCa6G50F7riGixERd/NPwO8QPipuKOGsSns0YvK8aBJAgIRIKGYOBnGszNDiSBAilDWQKBwKVOSJ0xKKkzF5Q5Dliv/mbC8n0ziYrvaT/Wh03UiX3Uxe/UR3KNE4if/M3nHJ/6Jm0v+pRjOS6Sv/m8ype+j6EsbdGOtwnKLn7Ptdtse/qZFX/xEj9ncPiSdup8Avtpv9wPmPMvpE+1hBTsiseX+83P2FZ/Y5pry9stm0m40XbqwydVtvN36v+0rlgPjP2grjQmIkmaqd/LrLQXJvVHP0Vby2ViexyX60/aXrlfsT36FZnGPcdV+Skl3y3puFE3ZfEXZegTTOO2v7abZbn/0c6q/mM7x3F8f/bDofR/qIz+i+NJzmYxhpwIVTEeE8mcpyw+iPbH8R/qOAzVP3xH+xwb+xlJPXE+D7ae/uZPemyc27QX4yXmAT6jHurrL15ifdEHMJajjbTtMmPZ1IeUjTak9sQ+RVv6qxdia7neZuziM8qW/cPPWHag8RgOoq3YYCu01oiLP7iiOE6cIK4tvl18v7ixuH3bDzebkTV8WTIOJoMdAy3+vqSDmNZJfZFDqRMuzXo5NtZDwDIJUvJZrDsyHpt+V26zXO9Ax6ccjE2xnmbb0+/9ij/u72ERYBIPpv0q9mdXbqzSYwfTFt+V24r2IiyqbM/VGesp10U9VXXF4yLTNsr1xzZiO2kbKWM9qZ/KZSJjW/G4HGNZyBl/bCf2a7B+SpnalCufKwOjTeX+NFN2sCy31W//Q/vN2lCud7j6kCP1x3wY7RgsY1lvLyy1MVRGu5bUPxwT64hjNNR6KBsZy8c64u/psbHN/uZKlR1pfWm7zdo+kC05e5oZR29XUu9g7MrZ1GzZ4eJ5HfOlsXYQNwmai403NBhaDE2GNhsR8beyuJb4NvG94sfFbdu+/C8nFQPTYmTAatQgpn/njm+GdfVFhs9yxzfL4ar3zc5pO/l/bZaidtmXV6BwT0m8zJ8rbzQaW4+1fAiVC7l3bSDmcmdkrg2jsdWJtmpr2078hPg+Ee2FBhtR8TdWRPytKW4gbiT+u7i1OKntqu3/mDXeaBxOKulnxR8v8T0uiD9uzjbxZzQajcblhdfu+EZb+4TPSF9tI35MfI/4VhHxhxYbUfE3XlxDXE98l/hh8ZPirm1f/9B52Q4YjcNJib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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={-3,-2,-1,2,3,4};
b={-10:-1,2:10};
c={-10:-1,2:10};
d={-10:-1,2:10};
f={2:12:1};
g={-5:-1,1:5};
h={-5:-1,1:5};
pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};
</text>
</varsrandom>
<varsglobal><text><![CDATA[g=g*h;
base=pair[0];
exponent=pair[1];
squareRoot=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}
ans=a*(b-c+d) +pow(f,2) - base + g / h;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 361139  -->
  <question type="formulas">
    <name>
      <text>L62- a(b-c+d) +f2 - p(pow(base,p)) - g / h (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">{a}({b} - {c} + {d}) + {f}<sup>2</sup> - {squareRoot} - \(\frac{{g}}{{h}}\)</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<div class="editor-indent" style="margin-left: 30px;"></div>
<table>
    <tbody>
        <tr>
            <td width="40%">
                <p></p>
                <p>{a}(<span class="" style="color: rgb(255, 51, 102);">{b} - {c}</span> + {d}) + {f}<sup>2</sup>&nbsp;- {squareRoot} - \(\frac{{g}}{{h}}\)</p>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses.&nbsp; <br>There are two operations inside the <br>parentheses.&nbsp; <br>{b} - {c} + {d}<br>
                <p><span>Work from left to right.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(255, 51, 102);">{b} - {c} = {=b-c}</span></span></p><br>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="100" height="40" role="presentation"><br><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}(<span class="" style="color: rgb(51, 102, 255);">{=b-c}</span><span class="" style="color: rgb(51, 102, 255);">&nbsp;+ {d}</span>) + {f}<sup>2</sup>&nbsp;- {squareRoot} - \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>
                <p><span>Finish simplifying inside the parentheses.&nbsp;</span></p>
                <p><span><span class="" style="color: rgb(51, 102, 255);">{=b-c} + {d} = {=b-c+d}</span></span></p>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>{a}(<span>{=b-c+d}</span>) + <span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2</span></sup>&nbsp;- {squareRoot} - \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Next Exponents from left to right<br><span class="" style="color: rgb(51, 255, 102);">{f}</span><sup><span class="" style="color: rgb(51, 255, 102);">2 </span></sup><span class="" style="color: rgb(51, 255, 102);">= ({f})({f}) = {=f*f}</span><br></td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-Exponents.png" alt="exponents" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td>{a}({=b-c+d}) +&nbsp;{=f*f}&nbsp;- <span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> - \(\frac{{g}}{{h}}\)

            </td>
            <td></td>
            <td>Square roots are exponents.<br><span class="" style="color: rgb(0, 46, 184);">{squareRoot}</span> = {base}<br>because {base}<sup>{exponent}</sup>&nbsp;={factors} = {=pow(base,exponent)}</td>
            <td></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d})</span> +&nbsp;{=f*f}&nbsp;- {base} - \(\frac{{g}}{{h}}\)<br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.<br><span class="" style="color: rgb(204, 51, 255);">{a}({=b-c+d}) = {=a*(b-c+d)}</span><br></td>
            <td style="text-align: center;"><br><br><img src="@@PLUGINFILE@@/ooo-Multiplication.png" alt="Multiplication" width="100" height="40" role="presentation"><br></td>
        </tr>
        <tr>
            <td>
                <p></p>
                <p><span>{=a*(b-c+d)}</span>&nbsp;+&nbsp;{=f*f}&nbsp;- {base} - <span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\)</span><br></p>
            </td>
            <td></td>
            <td>Multiplication or Division from left to right.&nbsp;<br>Division can be show with a fraction bar.<br><span class="" style="color: rgb(184, 138, 0);">\(\frac{{g}}{{h}}\) = {=g/h}</span><br>
            </td>
            <td style="text-align: center;"><br><br><br></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f}</span>&nbsp;- {base} -&nbsp;<span>{=g/h}</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right.<br><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d)}</span><span class="" style="color: rgb(255, 102, 51);">&nbsp;+&nbsp;{=f*f} =&nbsp;</span><span class="" style="color: rgb(255, 102, 51);">{=a*(b-c+d) + (f*f)}</span><br></td>
            <td><img src="@@PLUGINFILE@@/ooo-addition.png" alt="Addition or Subtraction" width="100" height="40" role="presentation"></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)}</span><span class="" style="color: rgb(51, 204, 255);">&nbsp;- {base}</span> -&nbsp;<span>{=g/h}</span>

            </td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(51, 204, 255);">{=(a*(b-c+d))+(f*f)} - {base} = {=(a*(b-c+d))+(f*f) -base}</span></td>
            <td><br></td>
        </tr>

        <tr>
            <td><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} - {=g/h}&nbsp;</span></td>
            <td></td>
            <td>Addition or Subtraction from left to right<br><span class="" style="color: rgb(70, 255, 150);">{=(a*(b-c+d))+(f*f)-base} - {=g/h} = {=(a*(b-c+d))+(f*f)-base - g/h}</span><br></td>
            <td><br></td>
        </tr>
    </tbody>
</table><br>]]></text>
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xPO+2filBexvr1n27sttubjeeYELvCgvxNFuTnG5c2HnnkiSJVGWeddbOlRSwh7hZa+cuNa0r1dZdrGtdcUxVsvzIbLmxy992vMTvmGBdb2tXN9PlyOmFdsHk9F1g9V1kd+GeRpaOe1VkRfPXVH7O011q62YVN4Z+wK/5PGauMKwvy/zRdlWsmWZ+4Y9H79uabv1mMgDzWr/+8jYurjbNsXCyxPCuezJsvVxTFnZGmsbor2HbffcgCjzg5rml88IP5n6I6/PBLG7vu+hbj20y0zTBhMte42PKsaNx554NFqjLuvPP7RfprLO2gcYmlX92sJ1//VLnGRMkXitod9933S7PhvCZ32+1Ks+Em4yJLOxU7yFcXbF7POVbP5VbHLONCS0c9qxrf/e5vilQtnHnmeyztpcZrLe0849IivduVPjxx332P2nfLjKRZYVxlbNeG1ZOqT9wRSd8ua3tSFbjzzh82jjhigY2J2cYFlme5caVxWx4f2AV9jrWoMb31WO0PxpD6ZEehaazuCrbddhuyBUmcHNeURELgnnt+2nj6009v7LLLucZLTJRcZ1xo6ZcZVzfOOmukSFnGww//ztKfY7zc0s8q8qxq1pOvf6pc07jqqrpg22WX8wpeaTbcZFxkaVc30+fLGY/kqws2r6PaXupZZT66w/zRWjQ/97l7Ld3FRvw50zjP0i0p0rtdVey66xzjbON8O77UuPLJtGXSJxOvT9wRSd+uaMyf/5ViJLTHww//e2P9+q/Y2GCOMHYZY8zXbXOMPP64vyeSv2ed9XH7bnnBiDEa19PLNRZvWzv7H//4/fYdY4g+WWHckrFfnA6axuquYNt11yELNuJkeOaZnyqmWhnr1n3GBNsZxgtswb/CeKOlX2JcYVxjXFoSBynmzfuo5bvE8lxrnFvkWW3M2zA1rmlceWVdsD396ec1iWDbZRcXbG4DtufKGY/kqws2r8cF2y67uGDzelY1ucsuC4w3Gq+ydBcaLzbim5lGfINPw66cIJxhvMZIGQsszbIn05bt8zonVl+aX9yxuNK4rPG1r20uRtLYePjhx23Ob7AxMsfIGI65zjjeVsZLeX5ceeWnmmN6l13m2zHsDVtzeTtlzK2UuXQ7Ojvzw5VXlm9HYU0g3nqsYRwRrxRvtmeaxuquYHv609fYoiROhp/7XP2nqMBhh13eeOpTz2w87WkXGWdY2jnGZcaVxtXG5Y2PfSz/g/AbNtxned5mvMp4k6VdWuTL2zA1rm5ccUVZsG3a9Eur99yCVxQ2LDSuaqbPlzMeybe6qKEFr+OtxsuNN1qaBUbqCS42zrVj1xuvNl5jnGGcZd9jEz71svPlX2a8xPgOO04fUF6uHXyeaH1pfnHHImNhhXG+ibb8HM8B4faBD3yncfjhlLHIGHM3N+amkz5mU1xxxYiN6+uM19uxecblxqnEmZgXtDUY3+XS76js3A/V2Mv48bhPv8y2NMScGD/lvOL2QdNY3RVsT33qGhMX4sS5+slLDCk2bvxJ4ylPOct4tvFSS/dO4zzjCuMqI3lXNE466UNFjjIef/z/Ng49dEaSd6FxmXG1sWrDVLm6cfnldcH2lKec2+RTn3qF8SYjNmD7ZG0gX11QeT1vtWMI3BuNC4zUE3UtNy424j/smG2cYyQdPllp9LLz5V+QtGOWsV07ooxO60vzijse6WPGCWNhrp2Y5U+u2uHxx//LTsjutRM3xsv8ohzGVjpec/VuKXqdKS6//Hb77irjDCPjfKkR+3L5x+aGDa0nrNeu/aZ9t8RIm2PO4Mt83h2JDz/st8fQ/6efPmLf4Qf8St/n4s5Ki7ePNvOAD3zgmxavBux7+iTiYbpuiNsbTWN1V7D19FCoODGubgwO/ksxzcoYHLzdjp9lPNd4pfEm40LjKuNqI/n5//LG5s3/VuQqY2jos3b8QuMM4zzjEiN5I38njPTUtdK4ouDy5P8rGgMDny9qdSDY3HZ4hTFn/8TrgVV4HW81Xm680bjASDlRF/mWGRcZ8QOcb1xspHzqI53XW0Wr/MuM7zTONS41UiZlk28i9ZGu2v6UOV+Qr8q07siTKy9YLZO/af44Fsej3vh/mjZXfreYsyXX9qpN49mVlht5I38wrS+to5PycyQPZdH3s21ej9pC/J/FyOoM7JgMDX3N8g8aGVOMvbB7MjZNlu6/FAMD/2DfXWKMuUeMwWe5/GNz06bWfVgjI/9q3zHPIHGD+RT9kM+/Y7AsiAcGPm3f4QPiB77N+YDv8M8c40wj8fZi41XG643EH8Yg4yXNJ24/lGDbBri6dFYZIKD39PQb32IMwcWkrQouX2CGh79b5Cxj48af2vHzjO0E33hcbQvFd6yc35hNrV1A7pHYsOFnFkxGLQ02LbX/31kcdUxMsK22/F+wMn/+5Nkl4Axz48Zfmw3ftDQseC6Sqmgv2FY3+vs/VbJ9dPTH9j1lQV8E0oViIujvH0nK8YW9k/rG9r+LeHyxefNvi1Ja4EyaMgcHv2Jp8T1lEozHXsDpxwD29fbeat+7P3t73908jh9S26mfuvr6PlikHb+eqbK3971Pjrl0LADGA+0fGbmv8H0qmsOmvF3pPKMMz+v5R0but7b+rjjq7aaOGNutdk+2zeSlDMblbGvjQiv/nqK2zrFp02+sL95lZbAwM5ewLfojV2+3Sfurgu3v7bu3GweMNxjxWTcE2732HSdH1xlpL/MHH26Zcbdt0MdvioGBj9l3+AHfItrwQbW/+Rzja5YRn7FmINbwHSJ/OseJ2H12XbD5YBM7Z2/ve4ppWQb3n7lgO8fI2SsTkMlIgE4XJv6/0oL4B4qcdfT1MckvNTLpOdOq7hjkuKopGqoLZg4bN/7C2sEOW/nBCRds2A8RUgQS2hCBw+vq77+jFKjbgV3E/n7O5mcX37TgdSDYYtGgzdSzsikEU2za9LB9jy0ISNItLY5MHCMjP7D8CER2PnwBre801uvzPqj7HKHSic8D7LwMDNxheakf37JYhrgoj5ORkQeKXA7Px47PXU0hNB58AZ1tZAzF4lmtZ/JkLiCcOrElgG/7+t5r+WMXJnxbHd+ramOMPuntXdkcV+3gY4l+o83h28m01+epi0sWT/x4rdnOCVu5X8YDJ3P9/X9n+avjqTv9MDa9HSkGBj5k311kZPcZgUD78FMu/9hML+uNjHzPviNuMKeJf9EH2DAdbd0azPn3H+07/HC1kT4PQVzNx3fMS/xEPCBtOi+6N1fFrUEJtq3OoaFvF9OyjMHBD9vxvzZeYGR3ClGQnmGmZBIuMeH0qyJ3GcPDX7bj7NJdY2ShaCcYWkx3YzoBryUYHv5W8cnhgg0R1V6wIdbSHZ3xwGI1NFR/TYLX006wVQXUb+x7fPEOI0Ftodk/9ruy2mFw8FOWn91LFhS/XDV+fSxoLNxp8FxV2gGaKIaGvmpl4N+qsIg6coLtI1bnT4pPnWF0lBMJFmXaGjuGaT2TI2It3eGaCBB4/f2IBsZ2nNRUBUxdsPX2zrU6/0/xKQ+feyyUMaamIhjIg134jEUUH+LLq82Wm6x/vtMc353ARdv7LW9cnmdMUXZdqPp3HGNM8DfS5doQbYs81fR+LEVLsMVJIW0LUUGdtJe/UX9aVsryfVjsQPrOHZf2mD+pQM2VVbW5yrBhLDuiDNJgdzCXr+q7KtPy0vpz5UWZfC5fQSjvYBJn8EGsBWl+iG8YC8wDxkV6EhdtHMvOsGsybU/LSRm28f8oK2WkaVeu6JRg2+pMA1SAhwV6es4wnmkkELK1zbY2k4fBnStruS3a+beqb978iB3nsiiiiYVn7DPg6o5UAFE2OvrD5sLCrgCfx8KmTb+w8rikmxdsXPrKiTUWow0bftSsZ3T0XrO/7qMqvB7YiWD7lX3P4tIKgH19w5bus8Y7jPV32w0M/K3xfcb3G//O+CFjeu/OtUa/TFW/NJzWx4IWiw4Bysnlzxw2b36s6YORkY1Nbtz4UNtFfWjoS1YW7YnLZfQxPqBf64ItV87GjT+zdPc062rn94EB7q1stbcVcOtjqROOJdY2bfr1k21nPODLHFzADFt5CCAWKhY07IpFoC7Y8G2KaDtjPMZ2q3/xa5Qb/VZvy/iMvNjGGGA+4EfKv8p8cWOzne36OAVp+vq4VBKirSxU05MhRK1f1mbxTtOV25GeNIyO/sS+Iy2MseRMkQo2Thw2bXqkOOIgxvktDcQd6o845vVP5ISNEysfc/SD29Xf/8niaNjsbRwa+lbpRAw7+vrYmUxt4OrEP9rJ5r3N8ZHu7vL/sL239+ZavqrvUjKmo8wUcYuBX86Pvii3oRNs2PCQ5Sv7c+PG1gu72/u7bCdjZHT0p812psBvbAB429db2patubZTTiAdN319f9/8nN7aEbfTcFVovHLFlBJsW5UEihw2bNhkxxFrZxtZ6GOxKAe6MpfbxLqlKKGO/n4mHWeq3JCa7hRU7VplE6p+SW54+F/sGDtYiCLs8p2z4eGvWmDLLy4u2N7cTJcTbLkdJYRaby9n09RDXhd8iCReBtwOrbRclhlPsLHzd77xbUbqYqeD9CwE2HhNkbKFnp7TjVyipl9oOwKY/PiUOmP3bEFGsKX1xb2IrYWfwF4FYqKvjzTcm0e73N9xTyB+r8IXcPowRBt9TCCknpUmBO4vUtaxceNm8zv5sJO2eT1DQ6NFihZI621GtOE7Ai7jsjqWOuGq0kIT8HGAr2hzuf18v2FDvS0ITN/tDNEW88XrqS6eAfw2MICYYTeb9nvbvX76jN2NOGliEZzqwuL94bbhO8rEXsYePo0dt42Fhe3hJwPMrbjdgT6PcV8+8fJL4LSBuqiT+knbsi31EcLL00PmbWthTYFg6+9/V00AV8GlZy5B+5hhrnl5E4X3L3ON9rKj3ZpvbvNsGx/59975ZX38PNdsWW/pflYcGRvceuC3Y+ALYkWcEJT9R99ydaITETo6+oClp7x51obPFt92Br/NIr0VY4l9l+5O8sCGt9P7mrng8QY7EZQbM/MuB4Tr4OAXLB872NF2yqPtXl4aY2PcjIzkf7knhT9IE+Wm8crLFVN2XbCFo8XxyYMC9YUaDAxwTw7CgAUqdowITkwSBjSBokqOcVn0l0UpZYyOcj8ICzFPDTFB0p2Rll2Dg18rcrQwNPR5O0ZeFk4Ws1SoXGaB7H3ZYO2CLQQO7YiHAVZYwHh3kaoFFmlfMKMeFtBWPSxi7DDl0BK4pCWg4y/3TV6wRflc7kqDMAHuhiJlC77jySVq2hL36+BLFnJEMMGxvoCAfH2+8OOHanBnV8l9TP9XhSF+ZIG+zPqlvhPqPiQNCz9tiYVlRVvB5pfM8XlaFztL1Hep5avfHO+X2LEDX8diXh5LnbDaNwCh4r6i/YwH6kI0Rfvhpc22VuFjlcuYYVcImBXm1/yOYX8/L6VM209dsSOKAETUxxzEn5Q38bbm6bb5/KVs6mB++o5bfz+7j2PvMPsOF20OG4kRy2u+5RK4n1hQdgjtdIEsX5L0S/mMb8j4dmGAvSmGhzc0RW8n4BJ0by9jn/Lon8U2p39tdT3SZLrDxQkaMcT5S+OvkvGNTbR3rrWrdVKBkNmw4cfFpzpGRr5redjJXNLc6amCNjvrP9pPG3lYJOptCYzWWJjorSTDw+yEXW8nWu+1OvHBw02m4ApJ1Q/Dw3dbvrgVwwVPWbBxby3jlnlAX7cE+mRvPxgaIk5Eefgh1iLmcSqa6YPOb7UYGPiolUG51ROJGJeiU4JtK3JldicLbNr0c2NMToIZAYSJ7EFtLHImmAPBzxelVNC0JlyQ4JnCz+ARQkEWNAImwYCzegLGtRYEuB+oLNpoRzvBNjz8gyKVw4NhurPGgs2iicChjuA1FgweLHK14IIK+8gT7aNt7QRbiCFEFwIKu2LRnF+kbMFtoi20n0CJIOIsn7wEmljMlpWCF8jX54JtbD/QHvxAn4UfaBsLBr6fWVucyO8iJ+57RIj6Ap4TbEND/2zH2Dnk9THYiBglLwti9O2iInUL7Hi2nl4mgE9OyOTHG20PhjCkHtoc7ce2GTauy5fl/alo8uCv9MQkL9i8/W8yxutzEGv0EcKGuvBhulMRwrSbCwplYSP9xBjCZnxKvfm5lcLbjMhm3DAmYxxWBVt68zplh+Bo2VEWbJw4MG8h/g7B2n5XDLHNCRxjtrd3lvn3C80xmcLvTcPW2CHCry5UiXWBkRHEDHMOMjbp17hEnRdsqeDDZ97my0wQMdf+xf7Szivs+48VqfwS3dDQBrMXGxj7zDc/QazGGred+R+XofGHC4yqv7GFByf6+jjOuLrY0vxvK7N1ouECMuY24xWfvLM46hgYuM2+wwfEIOY2ZdEnjNPIVxVsnKATC/FTiGOfB1WxhogeHPxnay91U/bbm3bmTo4HBri3mhNUxhnj1OdDNeYF6PuhoS82fYlP+/vfWyvX53y0hfFQHZeiU4Jtq3Gi9yx0A4ODnGET2FmMEA1MNiZxy6404IGhoTvtewIFARPxQLBkYhEECHAELSbZjTZpW0EQIDp9IawLtupC7WfOCBTSImwImgQG8lBHkIlfDmjAAxr5U0HqAaozwRZnjL5TWUVLSIb/IgiSj6AduxXsbHQu2KoiouWH8Dd+QxyGH2gXIoz/z7FxVH9p8sAA94awsOG/6Gd/dUUKX+jxG2I3xAqLB/7Dz9RB385pBvUULthYPGhPBG9fuNLxNDbLl9ZAa7xhDwt0XOKkDtoe7ceu2bYIlx90Ae47/BbjwPul6mtvf+yckifajxBgEYy66Oe0j7sp1qoM8ZbuuN1ki/7NNeGTwv0Vt09g75LaOPTLvgjy8A1jkHqi3qpgYyGlDyACK8RVXbBhW3//WjsW45YTG8/L5dLUdv7f24uPw9et/qwLNuJHTrAxB+uCLcCuZG8vYxO/ME6xifwudvr61jdPbv0SKT4jLceY3/iI/+PPS5p+CPhl9zhpo/50fJVFtQtXysIG5n7YcFHTJ5Tlt5rQpvAF/XJdUYLDBRt+IC7kBBtzfF6p71xYRryOy+Xc51x+yI2dMK+fNoWv+D92X2zpq7GTMUH6WEN83g8MfK5I0QI7g319HKftUa63P/Up6OtjHKY74y4E6/NjZ2bXBZtPenF8ciPmdMPvjWPixOWT8o5BTkT6fTwsaky6EAEs5BHsg9xs/+kil8MFG4svYocAE8F5eU0YDg5+3L6nHgIzwYIFgoDA5E3rod52O2AENIJsnP2OJaBCGBJ4yzsx5KnC01fLxx7qiHzOzuur1+OLKgtU+JvAyGJG+vABdfKXvptb21X1hY5gHf3sYqMq2FoLIiSQpgsoeaIO7o8p30g+MvIt+55+ze3Y1sd7nXUhDdxPtB/7GTP4OrUn2o9diy3Q/22RswUeDGmNIYQeZ+xLrQ1lwebpqAumi3AItLS+tJ9z7ekmqSP6GDto/yzz+fcLy+vo719naejDEFb1h198bJEmhB1jKua/t60u2OgHyNhg3Pp8TOFijfoZRyz6+J5xgaAg3zVme/k9kYODn7Dv04Wf+YToaF0OHBn5tn0X8w67Y+eXMcEJE3m4Z7Qs2LDHX2VETGAeIcLCHvJzAkQ/0x7KYfzyPeUzBrA50s2s+b0ljklDGUus/R8vjjp8h4sxBfEfbaX8KJu/1BWM2yoYr+XXFg0M8DANfqBeyqGPow34jrYuLPWd31ZA25lD9DVjYllzNzFA3OjtxX7sCzFFu1IfXG3llk+u+/t5fyPlYgP1c3JQ7gMXzIhFYgR2MCbIQ9nXNHf0Uvh4oJ+okzKJ89M137YXSrBtJa6oCZbpAE+f9vYyETlDI0Aw0VnMfFJUF1AuN7mAqi5oBPrIF4sZ7x8r3zjrgo1gS7AJweYLexV9fUxQ6kFQVhfqqMPr4bsqvJ5uCbbcLx3EwtFOsLX6trP6Fljg+0SRogXvHxa+nL+jrtTvBOqqmEKIUReLFLZ6/rxgi/6JtAR26qJtUc+yTB0Itpw/Ul+Mxfplcd+9wJbYyQzBxRig36PtLbvwYxUuxFiEUsFavikbeDrawKJCO2K3Im1/lbm2bElSp/dzTpwGfBeGBZ02s/DPt+/Kux6+K8q4YtHvVLAxHyFix8ctvkkxOMgTj/gx5i++pO/wPbbMNtv/pkjtGB3lHivSMsZDfC0ujTOelvU0tCuER9hAvKCf6i/s9l93YQxhD+OAvLErTn7qIg4RX+hvvwzpafhLuhBC7OCVT0R9vISApI2LzNbyT475ZVDGMvUzlpnXpGU8M8f4y2fqIxbzf77HroVFKY7WbnZ6EkIb8EHMjepDBwg2/Ma8RlgN1kTl8PDX7XvaQXsYF/Qbggl/hJ9usv4trwvDw7ywu9z+auz3eM7ONeMC27Ej2knZ5fuEXZwTsyiT+vE9435rzLltlRJsW4ErbALUb+yfLgwNfcZsIIgQQAhKIVTq2+UuNJjMBL8QeeQhQDCZyu3KCxXyE7hago1HvavwNARYAkEEpVg4y/VQdxWevyogsHFLCrZcQOlcsFXTgby/8UHV38Gltvg9WOR2uFBGaLNQhDBfbEExJ9jiEhbjgQWjembr/88LNuyMxR9/TEywVe1pjRcYArKdn70Mxkj11yBagjX6ygVrXbDFzgULSgiSdBxU69saDFuYC+WFPIULNtrSmmfTJdi8XOqGlB2LPuKD9NQzWDpJ9b5m7MXJGWOPXdBUsCE6sJf6QxwwHlyo+Xir3zPaijmQMcAccBHrtiBygtiHnSGimG/UEbbjx6pgo1ziFLazO1fe3eLeOT9OOuYgcz7GcohN/rog9DpdqPmx8i0ZrSeYKQtRSZ7ou4gN5R3knGAbHi7vFPb3v9u+p9zYuYt+S/2EnXOLHA6e0PZ85KFsTg4+Uxx1+PzjxJO+ow+wm/ETts8tjQcX5yHMJ7NjvzOw64ItgovYnsttwOffuTU4yA2yf2V8o5EbwTlD4TIhQmZi5Ifjc+B7DyStwB6BL7+AIlJCQMQWeASKcrvaC7ZYgJmInLHW73fwNExwghKBg8md2+lgEo8l2KoCot1DAKQnQLAQEKgJTF72xMqPoNKyr7P66jsgoOXvCIa+kNXrCXKps3x274KN+ljs8KUHyfaCjXSIZNKxYKR1uT/ygo3+qo6LdnZWWX8Iov2ObM7Pwdzl2m/Y9/g6bPNFMi/YcoK10zZMJ/FB+1/k4B2BrXHjAmigcpnKhRVtTf3CHKP8ej/7uGXhjRMNH7dVO7xc/M3iHDtmnq7Vd/g/LRsxSF9jS8z3nOgIwYZgrM5Ttzsv2LCHtkY+7Albgu5TfMB70YaHv9c8+cEGpz/IVf0lDC8/FSwLmukCLaHLOEasxPyIeFav38n/3WcpXLDhh1y/BXO+Y2yHYOU1G+U40epbGDtbzLe03/jLSVHLB61xEfNmjtlYFbW0n/6N3UXGhItRLze3m5r6a7y4tzNSgm3a2dtbvjQQ8JflItZ43xcLYSyknKkx6CfG6s2iKfr6WJhJx0QOYVS/x8knJpMOMpHiLDEmc9q2bgi2ToQKn3d0wRb+dn/l6wkus0Wm/KSo/6wZ9aVCZEGtf12wYROXWjgDZlHjrDot3/2RBldQFmyxEziRADuWYGPsc/9LLPxuQ76cpbUdNn/ykzJijFNGO8FG+5ljiAYWq2r7txXS/m1ZsLFAx+44Y4FdlOg3WF6gW4KNPmrtqHdHsDH2ycO4jhOWEOKtfHBw8Ku18TMe3M+UH34s31PrbcNnjMHYMcKGdH6ELR6jWnPc/5+iO4Jtdu1BLz9OOyjbhVe538LO8i0R9XExy2ws/yyhjzP6gfGYrjPRzvKJVl2wTTSe7AyUYJt28vbtHPyBAHbWWASZCAx0JhEBhwE/UV5jIjD/VNnwMG/EZ0IRBDmr8jOfauAjf1lAdEew5RYef7EvgTCCkgRbp4KtKkRciFHf9ijYGCssJPgJwVZdoKusjyW/PDhRwUb7t23BVh1XKXxHfmsJtlRQhL/HFhQtwcbYiziEqOuWYCNfzNWcwFnR9krHeCg/Ve3tTdHyW8z3Tk48ghzfMoKtOv7dT/g2nSe58c+4qPYd7aN8TqxuMBurgg17OZ4K1jSO5ezFnrBXgq1OCbZpZ/UsJzA4yM/9xI+9MzE56ySIEaQYvBPlLAtIPy1KL2PzZt6SHZOZgOYTNbcg+KPxnQiIqQm2wUFenpheYtvxBVtv761FihZcRExMsFVfAOr3KVIfizPjaNsUbOxuVDFRwdbXV3+tSV8ftlBGp4JtrPZPhWG3j0P3T/Rlvj3tuaytwPD5zM484ybdyd4ago1ySTMRwUbZ3RRs9D35Ir7VBc7g4IYitYP7qYaHv2FlEYeZ45D2+DvJUtQF27zMJUOOx3zv5MQjyPEtI9iqO/E+1zoTbOkupPcd+Sh/LMFG+9N70tI4Np69E40nOwO7LthiQIo55m62B345lJd3EnQJqAQw7t9hYsZ1/4lyoQWlLxU11OHvTGJSxSUMDwJV1IVUTKR04YHLaguwBy6CMoGBiehn/tRTFQCjo9+377n/jgDOriLBmeARk7ZVT07oeB2xw0CQDsHHU2Tlnaz8Tg7BKhbWcsAE7cuv+6Gz+ghg9bet+y9SpDuN7fzt7O8vv/sOuGBBsMWlvhBs5XtYWoItvSSYXjqC7o+8YKO/CPaIneolj/G4LCu2fLzhq7LAb1cu9x2l8BdEp+9VCwGRE2w8JTpe+yfLZU0RQJ3+u5GUC2NMd+onZ85XgeHhuywNsSP85jfn1wUb7+djoQ2hEQs0ddT7OS88fNymKAvBarnBJU1/BPznzRjn+J6ysbn8xHNZsPmlt/I8dbur883HflWwle0p/7Zl+noL6qK9/KWMC638nGBjfMXYn1uy25925njqt6rd7cjxqiDuzL91AYQfiFfYyE+dVZ9kpRzEeLSDvq2WC8vx0C9fko82uiDjZ89SuL1xPK7MpON+PHsnGk92BkqwTSOXWWAtv8YgsGEDv/sW967F5AnBEoN2oiTvwlKQTOHCgIDCGRJnt0yoxaUzReD3Q+UWZiZfq308Ml6tq3VPEgtJKtjqTzb6QksgJEhyNk2Qow3lergHMHfPidez/Qk2fsQ5hb9UlDRj+ztY3bH1xSIEC2UQ4KmLhw62LcFGm6qC1X3ViZ99LNQFL8Kf9tOudMGeXsFWHQP8rmJvL8fwk/dHq1/dx7ly+J4TlHb3WfmrejjJoS/SnbB5NTHvr99AiKTjIhZot2Eygm1w8GP2HQt0jAViSdmPVVt80aefsT0uidJHOcEW7coJn8kJthT+zjRsp53RDoQvdl1t5Y8UKR0ep1OhM9fGXfln0lq/g+s7UO63dv2cfsf/2wm2XL8Fxxdsg4NfKY46/PUntCPGf73fsKe6G+nvzCRfjAtemp67h02CrbuUYJtGLmsbdP3pUBYZBmxnOwvjk7xLaoEk8PDDv7Xj6cLIBFlsorL8gkvg9wQxAQma2BYB0INLTqwBX3wJboipEGzerv7+jxapWvCn+wgE+ACbCEwEEK9nrIXL69lygs0XuxDUBE33l9fRygc7F2zYVn6BJHCRjL9JG/7GD2ldS7P3Q/Jj7S58WZjxIz73/NuiYONHqqvwS7rYxP13LOTxioFou+fN/XC37xpgV/jPd27IvzUFG0CM8xLWvr53WZrY1a6OobQcH0tVUZpiZIR3afGwEnMs2sHYp+yysPLXMYRgo8/S9i6rjadOBRvt8peppvXj81Z7qn3l6UOw0c+UXX4wgZ8w8n4kJuTmactHKcYXbOX5PTj4SfsOvzBHaQN1McepD6FzV5HS4elIHzte82ppWi/9HS+eR1tSlgXb8PBX7Tv8MDXB1tt7c3HU4SfJ9C2+Sh8WwYaWfWm5fkJJH9Mn+MBPECTYpoNdF2wx4MQqc5eugF8O/UtjeoYcgYkBngbziZB8PK5+e1FTHYOD/C5c7GixMC6wyThUE1/Y6Gd5MZkIyNjHu73KIiCFCxXEQ1VIMRHrL3wFHpxisfadAurh7LDdbiHwehBUcRmM4EM99bdwu10scHEGTNupJ/zNk4flnUZfvOgjbPP7C/v6uMTEguf1hM87r488/AZg+ceeAT+b1NfHJCU4Erzc37C395as31uXoPEFAZOxFIKlnWDDpgjYBNUI2Ok44n6TdoItdwk7zd+O7qve3jXZfmXB898fZIEKAUL5S8wvH8zeC+o2MdYYB9hFm5hL9FE7wTZe+yfH6hioYuPGn9tY/7al+6S1k5+doW76mPfzfbZ54pSbHyn83rW4lYLYweIYJzq0o/w6BhdWt9j3jI24J8zn18jIpiJVCz6eWETTcYud9RdXt8qOBZr5h995qWrZF/5CboQCY5X52ho/aZs9HaKA+uPkI8r1sQCr5bvNtJGY07ok3uqfsiDasOEB+w57EGKIIsYCIouXzd5eG58+xvB3CF98Un7PnPuDX38gDe1jHPo89DH8d83xyJWG6Pe0XSlcaFNfKqzIk8ad3O5kCKDw7yIra3ORwuFl499qv7kd1fve/CevKBd7IhbmXusRgi1OviPuR3zI3a9YtXci8WRnoATbtLE68AP+dCiCjeAVi1+coU5lsJIXzrfAl/9BeK87nVQEgfk2eeq7HoDLbfzEDLsEPNBQDWT83mT6I9X+4+/tBBuBvPyyxQBnfqOjP2zWMzp6v30u7zBQ78aN5TN236HsnmCrXrIF2IWQIGjFbx5yZu1tikWyvkCNXR9vsL+t5ssAPwuDH0ZGfmD8obX7l9m0LBB9fZRJPSw8+DvdCayL660v2OCC2u5EgDbRz97+e40/rNkR8EvB9H/sZMYCFONtegVbb+/6opYtA8Raby8LZvxwf12g0u7h4XuKHA586pcw3T/4vuqXQH7c5gVbgIW3rw+hcoPZN2SfN9XGq9dPmSzQsQvm87UqHBFT/usfl1h/fczaw8KOuKGffFxX59vYgi0/nv1EMezhB/dX1mwJ5AXbXEtfjpv4mku/fX2r7Tht5L7Cz1ibWrELO3zupDGkLFyB23e+2TVo/vuC8Yv2mTZFX3cm2HKxBmHuu4yMH798Ozj4Zfu+PC4Q0L29tIP2I6QjxuReLizB1n1KsE0b213WGBh4rx3nLDkd3NUzwsmSwb7QxEf+sqjf/8KZdioUPWi0e8K0HRAWvb3XNyd/wAUbQion2DzIDA1N7FcfCBr9/e9pBsIUrXsAuyPY+vqGa4EtB8SEt4uFkrbxuo52P9GVqw8/LLQ2/UMzwE8GCEl/LQq+jss1XNaJBdb9sG0JNkhaxvk8Gwf1J0Y7BWPOx3HcVpDu0DKXqKd8CQZsScGGL4aGvl7U1F24WGM+ETcYVyyOcfmXMUg/+OLY27vWxkf+hK0KTrg2bGidqPi4Ze6m47Yu2BgLnWLDhh9ZfvqIHS3sZhe4NR/YtR4P3s4QOfX55uW3E2yQWxHqJ4vMP56ArP52ZjUO+Eko9qeCjTp4gW59t3wsjI5y+wPzh5ML2oQfGDt3FynyoB6POcQ58vA7rOMJNsbF/HHLzgHf8IP1Hlsol7bHDj67wtVfOpBg6z4l2KaFuftZgN9Hlj4dyqITl7AY3PnyJkZ+IPv9RY11+KLF2aLfi9BatHgMvPwaiBz8LJLJxsJ9gU3CVLAR8GPXI+5hi4kLmZCDFkA2dCRWCPa9vZTxNquzKtioh8UrgvR4gi0WjRA2qWDDb4jJ8QPbwAD3H7KYEbh9QcsLtnb1hR/mWNsWlxbMTsBvMvoOBOXjZ8QHuyf4AF/Tl15PXrBhEwKHIDlRwYbPY9Fqf0/f2KT91HmTLQhcJsq/9iYHxszw8AbLS7tpP2QcMpYZJ/iYhdrbXxds1Rfndlew+UL2iQm1aTz4PWvsyLOzhmBmAY3+Dvu9z5ycDNw+rmhjJ7O398bSvGrN37EFG/OO+w45ARwLo6P3WlrKih0qTq4YO+k4XWTp2s8B+tzjJDs7xMrZ5uOqWGAcjC3YqK+T+e0niOXfcPV4TR0x9hlnfkmTnbkNG/K/MlMFcx2fux9oE8KGuIWtc01Al2/LSEF/+UkGeYjbc0pztL0Aws+I3E8029YJGL99ffiM8ug/+i7GnM97Cbbp4NQEG4nJRGYKMcGGc8UqueemOvnYFRka+pQd52wNoRHBi4HKhI3BOlX6wjE6+oAFu/KZIoLRL6MxAdMdGern+1l2fJ3l/aHZX17sCOb8CHDrPW2+aHIJI+D3R8RiysRlESUgYZOLKQ+miJWFVt7dVm5L8IHNmx+x+r9ndpCuVc/QUEsE+82zfA8jSLcuBfJahbTtbhc2sVinC1HYhN/wwXyr912W/sel9rMw0f7W+87SRRPh8ZEJ1hd+wOZ3WJ1cjvlOs46qkKWt3N/mvqfPWFBh2IGfWcwYRwTnGEdLzN5vFqU43P5UsKQLZ9DtSx9GwabyQxjpuA3/dUrSY6OPNxYhXqOAEKX9VTAe8KfbHm2HLA6IVfzLAoEvy+1PL0XRBn+1zXjtnyypl7Lwy0xr0z9Z/a25MREw3rh9oa8P/yAWiBmMdRZFxh39zbG4DyrtA2yYZ2MFwf7dyjj+z6ZNAwP/YGkQuhfZ/1uvHvKHX/Ar9SCCqcMFW4xvFnP34Vubc5S+YYwGEAWcaA0MfKhIR6wJsUbs4F4x+j78jv1cJv98U5Sk8Et3n7Dj5GXse7v7+z9cpPD6vB7aE2KB8ik3fNLyCz9KPzr6rzW/8MDD0NAXLA11XfzkcY75eGOuEWuwAZ/EPZaMIV5z8ZFmu+tx81fNeNrXxwLMuGP+UAcnXfgiBJvHxeHhb1kZrdtM3LbN1mZ+B5T2IdrId5N9/6siFXP78/YdfuBEGRsjHlJ2jMtrLd0Xm+WlfQaw2/uNscG8or0xVyiT+dIaD8S8gPcB6ehn5mOcqFN/jM3FHdo70XiyI3Pygm0PowRbR2TAQQY2CzWBjwDIAkvg5S+fCUCcMfoE6N5ApRwmKYGA4EWAZ2IgfiLwMxmr9ROA+D/fERQIDkxcJiFBHFIOn7GfAEkAo3zKYuL5IuAkOOeESgQnjrHwk5/Jjk3VeviOYwQ47CEYpPVwDP/6DcPejqAHUreNdpCWYEnbCA7YkPqcPAQ2jiHEqCvaT5+FXXxHObH44Gfy8beT+qp+IAgSsMhHevJSTzviE9Lge/L4IlYfR/zlM3YRQGkP/UYd6cIWC2dK8mIbdhOo8T/tIX8EZMpN65sIyUO9Md6og3LpU+rItRvG2MMWxkHsUmAnbelW+yfDqI8y6Q/Gts8hxC67mwhSTpqq4DtuJ2A3rfX7wrETH+IUu+lvxiZton9y/ue76jgOn/rJjzP1JWXzN8YWnxm3LPLhV+YTfcV8Iw0kP39jbFAm9UQdMHyezhfGPmWGvXwOe4kH2BH20nbKZbyHyMEmbKNfY77FfOA7fEOZOb+4oHa/kC/md4wvSP3BaBNjE9vScYPviZv4hnrxDXOFPNgdPojYAfEVtuLfiI9hG3bTPnxFOaQnP36gTOzFbvwUc570+IX5kB6P+RmM+Rxtpz2UX7UzGPXRZuYntqbt5i+fY42JGIEPcutatJFyxrK3Op53ZqKxpibYDjGGYHttvhLRB11MkAiaITT4S2BhoEfgJX23BirlMPAjqDFBmVAECernb0wS7EvrJ8gx0QgGHGfyhd1MRiYYwTeCIxOZdExQ6iHQkCcWlmr5Vfs4jh/Ih42UTV3Uw1+CALYS3Cif4JTWwzE+Yy/lUW6Qz7FwUjZpw+8EWAJt2JTahb30C+mog0UXW8IHtJ3yKDeCZuq3ydZH2/AneagDX+CHIPXzXYwf6sHv5KVsbMiVj10EScqmLeSNxSLyRZ40L8GVvLEQ0R7yR/DmGOWndU6EYV+MA+rBLuqh32McVNuPb+l/xlf4H1urtkyl/ZMh9cFYyLANG7GVerE9FSKcQHGpsMrYVSZdiB3ajM2MkZhT1f5O7Qi/+q5Ka34xroJ8xhcsnviGv/QzaSH9EeOW8qgz5ivpgqQlL2VRJuOT8vkbY5XysT3iXdpXOXspN+ylDPxHHdiEDdiEbZE++pT/812Mh078wngLWyH1xtzFjmgXaWPOp/ONv3zGrpjDMVdSf0fZUU6IGvKGbdgdsYD2pP6MsRvxLvom5g71Ym8cT+cnpGx8T9vpw5hrOTshx7AVP1XnGf6MdnOM9lAe9VN2jNGom/TkIw/tG8/etN92ZnZHsP2B8Y+Nr7EO+/dWp4gtMvAYzAxCBiODmIHJIGUCpIE3JkGunMmS8ig3ghMTJOrnL/bEJMFO0gfDbvJhJ/aSjwkJowzKZNEjHZOQ8kjP97nyU9uiHuzDDwSvtB6CM38JBJTF8Vw95MGGdGFJy+d7jpOOciDlhN9Tn4Vtqd9y7cemtF7KIhDxd7L1cTzalvZV+CL8wXeUTRrSpvVTVrVsmLOLdlEfPiJvmi8YdsWCQL5qu6OOXP7xGHmr44B6YgGItlfbj/34lfG1pdo/WVJnOh7oJ+rEdhbcEG9xAoQoC/KZ7zlOOhY08uF/2ouf0nGeqx+GDaSlnbQ9/ApTP3IM32Mn/od8X41P0U8xLyIt+WNOUmaM3ZgnfB99RVnt+iqdBzEOohzKrJZDWv4fc4Y86fGcf6r1YHvMt/AL/48xEr6I8mPORTuiTFj1D22nvCDl8h3l4NvUH9Vy0nET/oz82Mxx6iI/5VBetCVspI1RZpSfjsucnRHfqCvKwk/kqfqUsvgubKVd5KHcdJxG+qifY53YK5rGem2htdBcaK/9jGixjgQbiX/feJTxFcbTzPEP5isSfXAyaJlQDHoGMoOTwZpOuC01QGNCUQ/1Uy/1Y0cEDOwjXZovJhZ5mUTkx15IOfwlL8fIT7poa6SHuUlerQeShry5eiDft6sn7IhjUSZM20A6GGVF2nZ2pXlzdvFdtd6p1JfLH/WlbFd3rlyYK5f8ndrFcdJFHvJ3WnenpIxqXam/07ZH+0m3pds/WUZ7qJM6qBP7mXuxQIY4aCdKU7FDPvJj80T8Hm2PdlMGcz8YcSj6lL/h4/BzWh9/q/1DHhjfUWbEubSOTvyd2kueqr3VcsK/fBfjI45TVif1tPNLlBc+ST/n2hFlhj2kTX1R9Qd1j1dO2EaeNH/YEH0TdUZ6/lI+x9OyJ2InTMuq2lkti3Thp+gDjqXpIw92dWrvzky0FZtiTa3VkWCDTzPuZnymcV/j84wvNB5v/NOenoFP5CsTnQzAGNhVxrFcvm5xsvWneSIwVhkBI62D74Lj1QGreaPsCGjj1VM9Xi07LTfypGWl6VNG3jR/ylw5kWey9VXzp8z5I8rNlZeyWm7VrlyeYJo3zd9p3Z2Ssqp2QtodjO/S+juxoVouf7dEG3IMG9P6Y6GMBa7KOBYL31RtTW2oMo7l0sR37cqK/6dM8wfjWFrOWJxIWWna+H96fCymeXNMy6t+hmOVCavlBcfKHxyrjGr++Bzp089pmSnTNNXyU3ZazmTyRL70cy79zsqZd5vGOtX48kJzsVmGBkOLocnQZm0F2zOM+xifazzC+DLjKT09/3Nh2eFinelgrjKXvtvM1RvMpRdFsXtM51uItlSIQsRZ9btUrE11rqY2VDlWmrSMsdKNx1w5YzFXRnC8tNXjY7GatxPmyqkyly9lLk+VuXzBTtJW0+SYy1dlLl/K6cqzsxFt1fNq4x8ZjzSivdBg4wq2XY0Itr2NBxsPN77EeJLxL+xs8Df5CkVRFEVRFMXOOf9xk1pnmL462fhS4wuMzzEi2NBi4wq23Y3PNh5oPMx4nPGVxv/W0/Omm/OViqIoiqIoip3z/H9ybdVzYqG10FwHGdFgaDE0GdosdFoT/AcFt4uRm9z2NMaTovzaQfHgQc9f9fTc+NN8xaIoiqIoiuL4REsd+FbTVfHAAVqLV3rwS1N7GdFiaLInd9cCIdh4GoEtON7/wU1vXEvlmipbdVwW/fOenhde3tMz74n8tWlRFEVRFEWxPdFQp8w3TfUXxrgcygMHaC6eEEWDocXGFWxswXGzG1tybM0933iMkZe6oQT/0sqelTdCFEVRFEVRzBOx9mdrTEv9lZH3r/2J8VgjWgvNxTMEaDC0GJoMfVYSbIAvuFaKouPaKZdF431s6S7bG4yn9/S8ZLCn5/qH8gaJoiiKoiiKLaKZ0E49f238cyO7a7yJg921eP8a2gsNhhaL+9dqSHfZ2IpD4cXTooca4142Hj9lG48nG87r6XnT7f5IuiiKoiiKoljm3CdcK+0zUGin/278UyO/bsAVTB42QGuhudIX5o4r2NKnRbmOiuLjuiqPm/IUA5dGqQjRdrrxHOPbe3pOfU9Pz8Xf6OmZ9WjeYFEURVEUxR2dc/+jp+e6n/f0XP49k0ofNB12temkc43srCHWeFEuWuoPjbzvlh8q4EHP2F2Lp0Nr96+lqO6y8R4Q7mWLJ0a5NEoFIdq4PPpG41nG84wXGy8zXmHEwGuM7yg4UxRFcSfitRNgLr8oitsHQ+egedA+aCC0EJoIbfRmI1qJy6CINe5be7ExLoXyZGjcu5Y+bNCRYIt72eK3RSmI97Kloo3Lo9zTxk1z7LZhzJnGs40oyfONbzNeaLzIiOGiKIqiKIo7EtE4EM1zgREN9BYjmghtxK7a64zcs8ZlUDQUYo3XeMSDBlzRjFd5jLu7BjiY7rLFpdFUtPEQApdHue7KzXIoRYzgCVJ23P6H8S+NbzL2G9kChFy3xXhRFEVRFMUdgWgbiM7hNjG0DxoILYQmYlPrFCM/QMDPT6GduAyKlkJT8asGiLW4FIr2CrE2pmADIdiqoo0CEW1s3XG9lUdQjzJyXxvCDdXYZ8QwtvwQcCjKPzPyJl/4elEURVEUxR2EoW/QOmgetA8aCC30KiO3kCHU2FX7AyM/+ZkTa1wKjQcNxt1dSxHKLrfTxj1tPIjAEw1UinBja4+nSDGI138cb+SSKSIOY9mFgyhMURRFURTFHYGhb9A6aB60DxoILYQmQhuhkRBq3FaGduK5ALQUmirdWZuwWAuEaKOAEG1cX+WmOJ5kQBlSKZWz48arPzCIrT523o42Yijbf5AXw4miKIqiKO5IDJ2D5kH7oIG435/bx9BGbG6hlbhCiXbip6fQUl0Ra4HYZYudNm6Gi6dHUYZUymVSdtwwBIN4BQgCDiXJDXUYG+RdI6IoiqIoijsCU42D5kH7INDQQmgiLn2ikUKooZ3QUGipEGuhs2KjbNKIAigs3W2jMtRhiDd23djiQ8BhGL9FipGQnbiUiDtRFEVRFMXtkVVdE3oH7YMGQguhidBG3KcWO2rx2o7qrtqUxVogJ9qoMIQbl0oxBIMgAg4DMTSIshRFURRFUdyRmGodtA9EB6GH2NQKoRY7altMrKVIhVuIt1TApSIuhFyVGC6KoiiKorg9s6pvQvuEOIOhjVKRlgq1LYqoJBiVVwVclWG0KIqiKIrijsKc5gk9lBNpwWlFtfJgKuJSpg0QRVEURVHcnpnTOsGcPtpukDNeFEVRFEVxe6cgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCNsBenr+P/GJbf3IDe/dAAAAAElFTk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</file>
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</file>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>a={-3,-2,-1,2,3,4};
b={-10:-1,2:10};
c={-10:-1,2:10};
d={-10:-1,2:10};
f={2:12:1};
g={-5:-1,1:5};
h={-5:-1,1:5};
pair={[2,2],[2,3],[2,4],[2,5],[2,6],[3,2],[3,3],[3,4],[4,2],[4,3],[5,2],[5,3],[6,2],[7,2],[8,2],[9,2],[10,2],[11,2],[12,2],[13,2],[14,2],[15,2]};
</text>
</varsrandom>
<varsglobal><text><![CDATA[g=g*h;
base=pair[0];
exponent=pair[1];
squareRoot=pick(exponent>2,join("","\\( \\sqrt{",pow(base,exponent),"} \\)"),join("","\\( \\sqrt[",exponent,"]{",pow(base,exponent),"} \\)"));
factors=join("",base);
for (i:[0:7]) {
factors=pick(exponent>(i+1),factors,join("",factors," • ",base));
}
ans=a*(b-c+d) +pow(f,2) - base - g / h;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L64- Reflections on the Coordinate Plane</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 361171  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Parallelogram</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s} to graph a&nbsp; polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};
randMove=shuffle([-1,1]);</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=4;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1+randMove[0];
Yb1=Ya1+length;
Xc1=Xa1+side+randMove[0];
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);


MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361172  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Quadrilateral-</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s} to graph a polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=3;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1-1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1-1;

axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);


MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361173  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Rectangle</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s} to graph a polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=1;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
					
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361174  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Square</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Use the points {s} to graph a polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5,1,1],[4,1,1],[4,1,2],[4,2,1],[4,2,2],[3,1,1],[3,1,2],[3,1,3],[3,2,1],[3,2,2],[3,2,3],[3,3,1],[3,3,2],[3,3,3],[2,1,1],[2,1,2],[2,1,3],[2,1,4],[2,2,1],[2,2,2],[2,2,3],[2,2,4],[2,3,1],[2,3,2],[2,3,3],[2,3,4],[2,4,1],[2,4,2],[2,4,3],[2,4,4],[1,1,1],[1,1,2],[1,1,3],[1,1,4],[1,1,5],[1,2,1],[1,2,2],[1,2,3],[1,2,4],[1,2,5],[1,3,1],[1,3,2],[1,3,3],[1,3,4],[1,3,5],[1,4,1],[1,4,2],[1,4,3],[1,4,4],[1,4,5],[1,5,1],[1,5,2],[1,5,3],[1,5,4],[1,5,5]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=0;
side=sideStart[0];
Xa1=sideStart[1];
Ya1=sideStart[2];
Xb1=Xa1;
Yb1=Ya1+side;
Xc1=Xa1+side;
Yc1=Ya1+side;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);


MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361175  -->
  <question type="formulas">
    <name>
      <text>L64-Graph Trapezoid</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s}, then identify what type of polygon it is.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L64- Reflections on the Coordinate Plane/L64- Reflections</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 361191  -->
  <question type="formulas">
    <name>
      <text>L64- Parallelogram- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};
randMove=shuffle([-1,1]);</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=4;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1+randMove[0];
Yb1=Ya1+length;
Xc1=Xa1+side+randMove[0];
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361201  -->
  <question type="formulas">
    <name>
      <text>L64- Parallelogram- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};
randMove=shuffle([-1,1]);</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=4;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1+randMove[0];
Yb1=Ya1+length;
Xc1=Xa1+side+randMove[0];
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361192  -->
  <question type="formulas">
    <name>
      <text>L64- Quadrilateral- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=3;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1-1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1-1;

axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361202  -->
  <question type="formulas">
    <name>
      <text>L64- Quadrilateral- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=3;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1-1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1-1;

axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361193  -->
  <question type="formulas">
    <name>
      <text>L64- Rectangle- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=1;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361203  -->
  <question type="formulas">
    <name>
      <text>L64- Rectangle- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=1;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361194  -->
  <question type="formulas">
    <name>
      <text>L64- Square - reflection- No id of shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5,1,1],[4,1,1],[4,1,2],[4,2,1],[4,2,2],[3,1,1],[3,1,2],[3,1,3],[3,2,1],[3,2,2],[3,2,3],[3,3,1],[3,3,2],[3,3,3],[2,1,1],[2,1,2],[2,1,3],[2,1,4],[2,2,1],[2,2,2],[2,2,3],[2,2,4],[2,3,1],[2,3,2],[2,3,3],[2,3,4],[2,4,1],[2,4,2],[2,4,3],[2,4,4],[1,1,1],[1,1,2],[1,1,3],[1,1,4],[1,1,5],[1,2,1],[1,2,2],[1,2,3],[1,2,4],[1,2,5],[1,3,1],[1,3,2],[1,3,3],[1,3,4],[1,3,5],[1,4,1],[1,4,2],[1,4,3],[1,4,4],[1,4,5],[1,5,1],[1,5,2],[1,5,3],[1,5,4],[1,5,5]};
#0= x-axis and 1=y-axis
axisRand={0,1};

bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[side=sideStart[0];
Xa1=sideStart[1];
Ya1=sideStart[2];
Xb1=Xa1;
Yb1=Ya1+side;
Xc1=Xa1+side;
Yc1=Ya1+side;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361204  -->
  <question type="formulas">
    <name>
      <text>L64- Square - reflection- No id of shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5,1,1],[4,1,1],[4,1,2],[4,2,1],[4,2,2],[3,1,1],[3,1,2],[3,1,3],[3,2,1],[3,2,2],[3,2,3],[3,3,1],[3,3,2],[3,3,3],[2,1,1],[2,1,2],[2,1,3],[2,1,4],[2,2,1],[2,2,2],[2,2,3],[2,2,4],[2,3,1],[2,3,2],[2,3,3],[2,3,4],[2,4,1],[2,4,2],[2,4,3],[2,4,4],[1,1,1],[1,1,2],[1,1,3],[1,1,4],[1,1,5],[1,2,1],[1,2,2],[1,2,3],[1,2,4],[1,2,5],[1,3,1],[1,3,2],[1,3,3],[1,3,4],[1,3,5],[1,4,1],[1,4,2],[1,4,3],[1,4,4],[1,4,5],[1,5,1],[1,5,2],[1,5,3],[1,5,4],[1,5,5]};
#0= x-axis and 1=y-axis
axisRand={0,1};

bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[side=sideStart[0];
Xa1=sideStart[1];
Ya1=sideStart[2];
Xb1=Xa1;
Yb1=Ya1+side;
Xc1=Xa1+side;
Yc1=Ya1+side;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361195  -->
  <question type="formulas">
    <name>
      <text>L64- Square - reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5,1,1],[4,1,1],[4,1,2],[4,2,1],[4,2,2],[3,1,1],[3,1,2],[3,1,3],[3,2,1],[3,2,2],[3,2,3],[3,3,1],[3,3,2],[3,3,3],[2,1,1],[2,1,2],[2,1,3],[2,1,4],[2,2,1],[2,2,2],[2,2,3],[2,2,4],[2,3,1],[2,3,2],[2,3,3],[2,3,4],[2,4,1],[2,4,2],[2,4,3],[2,4,4],[1,1,1],[1,1,2],[1,1,3],[1,1,4],[1,1,5],[1,2,1],[1,2,2],[1,2,3],[1,2,4],[1,2,5],[1,3,1],[1,3,2],[1,3,3],[1,3,4],[1,3,5],[1,4,1],[1,4,2],[1,4,3],[1,4,4],[1,4,5],[1,5,1],[1,5,2],[1,5,3],[1,5,4],[1,5,5]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=0;
side=sideStart[0];
Xa1=sideStart[1];
Ya1=sideStart[2];
Xb1=Xa1;
Yb1=Ya1+side;
Xc1=Xa1+side;
Yc1=Ya1+side;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361205  -->
  <question type="formulas">
    <name>
      <text>L64- Square - reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5,1,1],[4,1,1],[4,1,2],[4,2,1],[4,2,2],[3,1,1],[3,1,2],[3,1,3],[3,2,1],[3,2,2],[3,2,3],[3,3,1],[3,3,2],[3,3,3],[2,1,1],[2,1,2],[2,1,3],[2,1,4],[2,2,1],[2,2,2],[2,2,3],[2,2,4],[2,3,1],[2,3,2],[2,3,3],[2,3,4],[2,4,1],[2,4,2],[2,4,3],[2,4,4],[1,1,1],[1,1,2],[1,1,3],[1,1,4],[1,1,5],[1,2,1],[1,2,2],[1,2,3],[1,2,4],[1,2,5],[1,3,1],[1,3,2],[1,3,3],[1,3,4],[1,3,5],[1,4,1],[1,4,2],[1,4,3],[1,4,4],[1,4,5],[1,5,1],[1,5,2],[1,5,3],[1,5,4],[1,5,5]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=0;
side=sideStart[0];
Xa1=sideStart[1];
Ya1=sideStart[2];
Xb1=Xa1;
Yb1=Ya1+side;
Xc1=Xa1+side;
Yc1=Ya1+side;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361196  -->
  <question type="formulas">
    <name>
      <text>L64- Trapezoid- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-8, 8, 8, -8],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361206  -->
  <question type="formulas">
    <name>
      <text>L64- Trapezoid- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-8, 8, 8, -8],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361197  -->
  <question type="formulas">
    <name>
      <text>L64- Trapezoid2- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
Xa1=Xa1-1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-8, 8, 8, -8],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361207  -->
  <question type="formulas">
    <name>
      <text>L64- Trapezoid2- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
Xa1=Xa1-1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-8, 8, 8, -8],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361198  -->
  <question type="formulas">
    <name>
      <text>L64- Trapezoid3- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
Xa1=Xa1-1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text><![CDATA[crita=((_0==Xa) &&(_1==Ya))*.25;
critb=((_2==Xb) &&(_3==Yb))*.25;
critc=((_4==Xc) &&(_5==Yc))*.25;
critd=((_6==Xd) &&(_7==Yd))*.25;]]></text>
 </vars2>
 <correctness>
  <text>crita+critb+critc+critd</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-8, 8, 8, -8],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361208  -->
  <question type="formulas">
    <name>
      <text>L64- Trapezoid3- reflection-Id Shape</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the reflection of the quadrilateral over the {axis}-axis.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
Xa1=Xa1-1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-8, 8, 8, -8],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A1',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B1',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C1',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D1',
                fixed: main.solved
            });
						
          var X1=brd.create('point', [{Xa1}, {Ya1}], {
                name: 'A',
                fixed: true,
                color: 'orange',
                visible: true
            });
          
          var X2=brd.create('point', [{Xb1}, {Yb1}], {
                name: 'B',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X3=brd.create('point', [{Xc1}, {Yc1}], {
                name: 'C',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var X4=brd.create('point', [{Xd1}, {Yd1}], {
                name: 'D',
                fixed: true,
                color: 'orange',
                visible: true
            });
          var poly=brd.create('polygon',[X1,X2,X3,X4],{
            visible:true,
            fillColor:'orange'
          });
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A1',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B1',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C1',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D1',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #8/L64- Reflections on the Coordinate Plane/L64-Graph points- Quadrilateral</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 361215  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Parallelogram</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s} to graph a&nbsp; polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};
randMove=shuffle([-1,1]);</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=4;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1+randMove[0];
Yb1=Ya1+length;
Xc1=Xa1+side+randMove[0];
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);


MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361216  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Quadrilateral-</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s} to graph a polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=3;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1-1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1-1;

axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);


MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr">To graph the reflection over the {axis}-axis keep the same {axis} value and negate the {nonAxis} value.</p><p dir="ltr"><span style="font-size: 0.9375rem;">point A is at ({Xa},{Ya})&nbsp; therefore the reflection is at ({Xa1},{Ya1}).</span><br></p><p dir="ltr"><span style="font-size: 0.9375rem;">point B is at ({Xb},{Yb})&nbsp; therefore the reflection is at ({Xb1},{Yb1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point C is at ({Xc},{Yc})&nbsp; therefore the reflection is at ({Xc1},{Yc1}).<br></span></p><p dir="ltr"><span style="font-size: 0.9375rem;">point D is at ({Xd},{Yd})&nbsp; therefore the reflection is at ({Xd1},{Yd1}).<br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361217  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Rectangle</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s} to graph a polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=1;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
					
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361218  -->
  <question type="formulas">
    <name>
      <text>L64- Graph a Square</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Use the points {s} to graph a polygon, then identify it.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5,1,1],[4,1,1],[4,1,2],[4,2,1],[4,2,2],[3,1,1],[3,1,2],[3,1,3],[3,2,1],[3,2,2],[3,2,3],[3,3,1],[3,3,2],[3,3,3],[2,1,1],[2,1,2],[2,1,3],[2,1,4],[2,2,1],[2,2,2],[2,2,3],[2,2,4],[2,3,1],[2,3,2],[2,3,3],[2,3,4],[2,4,1],[2,4,2],[2,4,3],[2,4,4],[1,1,1],[1,1,2],[1,1,3],[1,1,4],[1,1,5],[1,2,1],[1,2,2],[1,2,3],[1,2,4],[1,2,5],[1,3,1],[1,3,2],[1,3,3],[1,3,4],[1,3,5],[1,4,1],[1,4,2],[1,4,3],[1,4,4],[1,4,5],[1,5,1],[1,5,2],[1,5,3],[1,5,4],[1,5,5]};
#0= x-axis and 1=y-axis
axisRand={0,1,2,3};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=0;
side=sideStart[0];
Xa1=sideStart[1];
Ya1=sideStart[2];
Xb1=Xa1;
Yb1=Ya1+side;
Xc1=Xa1+side;
Yc1=Ya1+side;
Xd1=Xa1+side;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1,Xa1*-1,Xa1);
Ya=pick(axisRand,Ya1,Ya1,Ya1*-1,Ya1*-1);
Xb=pick(axisRand,Xb1,Xb1*-1,Xb1*-1,Xb1);
Yb=pick(axisRand,Yb1,Yb1,Yb1*-1,Yb1*-1);
Xc=pick(axisRand,Xc1,Xc1*-1,Xc1*-1,Xc1);
Yc=pick(axisRand,Yc1,Yc1,Yc1*-1,Yc1*-1);
Xd=pick(axisRand,Xd1,Xd1*-1,Xd1*-1,Xd1);
Yd=pick(axisRand,Yd1,Yd1,Yd1*-1,Yd1*-1);


MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>randShape[_0] == correct</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 361219  -->
  <question type="formulas">
    <name>
      <text>L64-Graph Trapezoid</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Plot the points {s}, then identify what type of polygon it is.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>sideStart={[5, 3, 1, 1],[4, 5, 1, 1],[4, 5, 2, 1],[3, 5, 1, 1],[3, 5, 2, 1],[3, 5, 3, 1],[2, 5, 1, 1],[2, 5, 2, 1],[2, 5, 3, 1],[2, 5, 4, 1],[1, 5, 1, 1],[1, 5, 2, 1],[1, 5, 3, 1],[1, 5, 4, 1],[1, 5, 5, 1],[5, 4, 1, 1],[5, 2, 1, 1],[5, 2, 1, 2],[5, 3, 1, 2],[5, 3, 1, 3],[3, 4, 1, 1],[3, 4, 2, 1],[3, 4, 3, 1],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[3, 4, 1, 2],[3, 4, 2, 2],[3, 4, 3, 2],[2, 4, 1, 1],[2, 4, 2, 1],[2, 4, 3, 1],[2, 4, 4, 1],[2, 4, 1, 2],[2, 4, 2, 2],[2, 4, 3, 2],[2, 4, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[1, 2, 1, 4],[1, 2, 2, 4],[3,2, 3, 4],[1, 2, 4, 4],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 1],[1, 4, 4, 1],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[1, 4, 1, 3],[1, 4, 2, 3],[1, 4, 3, 3],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 2],[1, 4, 2, 2],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 1],[1, 4, 1, 1],[1, 4, 2, 1],[1, 4, 3, 2],[1, 4, 4, 2],[1, 4, 5, 2],[5, 3, 1, 1],[4, 3, 1, 1],[4, 3, 2, 1],[4, 3, 1, 2],[4, 3, 2, 2],[2, 3, 1, 1],[2, 3, 2, 1],[2, 3, 3, 1],[2, 3, 4, 1],[2, 3, 1, 2],[2, 3, 2, 2],[2, 3, 3, 2],[2, 3, 4, 2],[2, 3, 1, 3],[2, 3, 2, 3],[2, 3, 3, 3],[2, 3, 4, 3],[2, 3, 1, 4],[2, 3, 2, 4],[2, 3, 3, 4],[2, 3, 4, 1],[1, 3, 1, 1],[1, 3, 2, 1],[1, 3, 3, 1],[1, 3, 4, 1],[1, 3, 5, 1],[1, 3, 1, 2],[1, 3, 2, 2],[1, 3, 3, 2],[1, 3, 4, 2],[1, 3, 5, 2],[1, 3, 1, 3],[1, 3, 2, 3],[1, 3, 3, 3],[1, 3, 4, 3],[1, 3, 5, 3],[1, 3, 1, 1],[1, 3, 2, 3],[1, 3, 3, 4],[1, 3, 4, 2],[1, 3, 5, 1],[1, 3, 1, 3],[1, 3, 2, 2],[2, 1, 3, 5],[1, 3, 4, 2],[1, 3, 5, 1]};
#0= x-axis and 1=y-axis
axisRand={0,1};
randShape=shuffle([0,1,2,3,4,5]);
bn={1:99999};</text>
</varsrandom>
<varsglobal><text><![CDATA[#correct tells number of shape shown
correct=2;
side=sideStart[0];
length=sideStart[1];
Xa1=sideStart[2];
Ya1=sideStart[3];
Xb1=Xa1;
Yb1=Ya1+length;
Xc1=Xa1+side;
Yc1=Ya1+length;
Xd1=Xa1+side+1;
Yd1=Ya1;
axis=pick(axisRand,"x","y");
nonAxis=pick(axisRand,"y","x");
Xa=pick(axisRand,Xa1,Xa1*-1);
Ya=pick(axisRand,Ya1*-1,Ya1);
Xb=pick(axisRand,Xb1,Xb1*-1);
Yb=pick(axisRand,Yb1*-1,Yb1);
Xc=pick(axisRand,Xc1,Xc1*-1);
Yc=pick(axisRand,Yc1*-1,Yc1);
Xd=pick(axisRand,Xd1,Xd1*-1);
Yd=pick(axisRand,Yd1*-1,Yd1);

MB=join("","MyBoxH1",bn);
s=join("","A:(",Xa,",",Ya,"), B:(",Xb,",",Yb,"), C:(",Xc,",",Yc,"), D:(",Xd,",",Yd,")");
shape=["square","rectangle","trapezoid", "quadrilateral", "parallelogram", "rhombus"];
choices=[shape[randShape[0]],shape[randShape[1]],shape[randShape[2]],shape[randShape[3]],shape[randShape[4]],shape[randShape[5]]];
ans=-1;
for (i:[0:6]){
ans=(randShape[i]==correct)?i:ans;
}]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>8</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[Xa,Ya,Xb,Yb,Xc,Yc,Xd,Yd]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<script type="text/javascript" src="https://jsxgraph.uni-bayreuth.de/distrib/jsxgraphcore.js"></script>
<script type="text/javascript" src="https://code.jquery.com/jquery-3.1.0.min.js"></script>
<script type="text/javascript" src="https://moodle.itemspro.eu/moodle/aaimg/ajsx/jsxquestion.js">
</script>

<div id="{MB}" class="jxgbox" style="width:350px; height:350px;margin-left:1px; ;"></div>
<script type="text/javascript">
    $(function() {
        var jsxCode = function(main) {
            main.brd = JXG.JSXGraph.initBoard(main.elm.id, {
                boundingbox: [-7, 7, 7, -7],
                showNavigation: false,
                showCopyright: false,
                grid: true,
                axis: true,
                zoom: {
                    enabled: false,
                    wheel: false
                },
                pan: {
                    enabled: false,
                    needTwoFingers: false
                }
            });
            var brd = main.brd;
            brd.options.point.showInfobox = false;

            var t0x = main.get(0);
            if (t0x === null) {
                t0x = 3;
            }
            var t0y = main.get(1);
            if (t0y === null) {
                t0y = -6;
            }
            var t1x = main.get(2);
            if (t1x === null) {
                t1x = 4;
            }
            var t1y = main.get(3);
            if (t1y === null) {
                t1y = -6;
            }
            var t2x = main.get(4);
            if (t2x === null) {
                t2x = 5;
            }
            var t2y = main.get(5);
            if (t2y === null) {
                t2y = -6;
            }
            var t3x = main.get(6);
            if (t3x === null) {
                t3x = 6;
            }
            var t3y = main.get(7);
            if (t3y === null) {
                t3y = -6;
            }


            var p0 = brd.create('point', [t0x, t0y], {
                snapToGrid: true,
                color: 'blue',
                name: 'A',
                fixed: main.solved
            });
            var p1 = brd.create('point', [t1x, t1y], {
                snapToGrid: true,
                color: 'blue',
                name: 'B',
                fixed: main.solved
            });
            var p2 = brd.create('point', [t2x, t2y], {
                snapToGrid: true,
                color: 'blue',
                name: 'C',
                fixed: main.solved
            });
            var p3 = brd.create('point', [t3x, t3y], {
                snapToGrid: true,
                color: 'blue',
                name: 'D',
                fixed: main.solved
            });
						
          
          
           var ansA= brd.create('point', [{Xa}, {Ya}], {
                color: 'green',
                name: 'A',
                visible: main.solved
            });
            var ansB= brd.create('point', [{Xb}, {Yb}], {
                color: 'green',
                name: 'B',
                visible: main.solved
            });
            var ansC= brd.create('point', [{Xc}, {Yc}], {
                color: 'green',
                name: 'C',
                visible: main.solved
            });
            var ansD= brd.create('point', [{Xd}, {Yd}], {
                color: 'green',
                name: 'D',
                visible: main.solved
            });
          
          var poly=brd.create('polygon',[ansA,ansB,ansC,ansD],{
            visible:main.solved,
            fillColor:'green'
          });
          
            var check = function() {
                main.set(0, p0.X());
                main.set(1, p0.Y());
                main.set(2, p1.X());
                main.set(3, p1.Y());
                main.set(4, p2.X());
                main.set(5, p2.Y());
                main.set(6, p3.X());
                main.set(7, p3.Y());
            }
            check();
            brd.on('update', function() {
                check();
            });
        };
        new JSXQuestion("{MB}", jsxCode, false);
    });
</script>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr"></p><p dir="ltr">To plot a point: Start at the Origin: (0,0)<br></p><ol><li>&nbsp;The X value determines how far left or right the point is.</li><ul><li>If X is positive, move to the right</li><li>If X is negative, move to the left</li></ul><li><p dir="ltr">The Y value determines how far up or down the point is.</p></li><ul><li>If Y is positive, move up</li><li><span>If Y is negative, move down</span></li></ul></ol><p dir="ltr"><span style="font-size: 0.9375rem;"><br></span></p><ol><ul>

    </ul>
</ol>
<p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
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<text></text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {_0:choices:MCE}<br>Give the <strong>best</strong>, most specific description.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Quadrilateral ABCD is best defined as a {=shape[correct]}</p>]]></text>
 </feedback>
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<text></text>
 </correctfeedback>
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<text></text>
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</answers>
  </question>

</quiz>