<?xml version="1.0" encoding="UTF-8"?>
<quiz>
<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #5/L34 - LCM</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 358790  -->
  <question type="formulas">
    <name>
      <text>L34 - Multiples- LCM</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What is the least common multiple of {number1} and {number2}?</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>numbers=shuffle([2:11]);</text>
</varsrandom>
<varsglobal><text><![CDATA[number1=numbers[0];
number2=numbers[1];
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>"));

}]]></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>least</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;">The least common multiple of {number1} and {number2} is <strong>{least}</strong></p><p dir="ltr" style="text-align: left;">The multiples of {number1} are: {multiples1}</p><p dir="ltr" style="text-align: left;">The multiples of {number2} are: {multiples2}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358791  -->
  <question type="formulas">
    <name>
      <text>L34 - Multiples- LCM (initials)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What is the LCM of {number1} and {number2}?</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>numbers=shuffle([2:11]);</text>
</varsrandom>
<varsglobal><text><![CDATA[number1=numbers[0];
number2=numbers[1];
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>"));

}]]></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>least</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;">The least common multiple of {number1} and {number2} is <strong>{least}</strong></p><p dir="ltr" style="text-align: left;">The multiples of {number1} are: {multiples1}</p><p dir="ltr" style="text-align: left;">The multiples of {number2} are: {multiples2}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358792  -->
  <question type="formulas">
    <name>
      <text>L34 - Multiples- Parts</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What are the multiples of {number1}?</p>

<table>
    <tbody>
        <tr>
            <td>{number1}</td>
            <td>,</td>
            <td>
                {#num12}</td><td>,</td>
  <td>{#num13}</td><td>,</td>
  <td>{#num14}</td>
      <td>,</td>
  <td>{#num15}</td>
      <td>,</td>
  <td>{#num16}</td>
      <td>,</td>
  <td>{#num17}</td>
      <td>,</td>
  <td>{#num18}</td>
      <td>,</td>
  <td>{#num19}</td> <td>,</td><td>{#num110}</td></tr></tbody></table>
  <p dir="ltr" style="text-align: left;"><span style="font-size: 0.9375rem;"><br></span></p><p dir="ltr" style="text-align: left;"><span style="font-size: 0.9375rem;">What are the multiples of {number2}?</span><br></p>
<table>
    <tbody>
        <tr>
            <td>{number2}</td>
            <td>,</td>
            <td>
                {#num22}</td><td>,</td>
  <td>{#num23}</td><td>,</td>
  <td>{#num24}</td>
      <td>,</td>
  <td>{#num25}</td>
      <td>,</td>
  <td>{#num26}</td>
      <td>,</td>
  <td>{#num27}</td>
      <td>,</td>
  <td>{#num28}</td>
      <td>,</td>
  <td>{#num29}</td> <td>,</td><td>{#num210}</td></tr></tbody></table>

  <p dir="ltr" style="text-align: left;"><br></p><p dir="ltr" style="text-align: left;">What is the least common multiple of {number1} and {number2}?</p><p dir="ltr" style="text-align: left;">{#least}</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">The least common multiple of {number1} and {number2} is&nbsp;<strong>{least}</strong></p><p dir="ltr">The multiples of {number1} are: {multiples1}</p><p dir="ltr">The multiples of {number2} are: {multiples2}</p><br><p></p>]]></text>
    </generalfeedback>
    <defaultgrade>19.0000000</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>numbers=shuffle([2:11]);</text>
</varsrandom>
<varsglobal><text><![CDATA[number1=numbers[0];
number2=numbers[1];
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>"));

}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#num12</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*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></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>#num13</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*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></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>2</text>
 </partindex>
 <placeholder>
  <text>#num14</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*4</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>
<answers>
 <partindex>
  <text>3</text>
 </partindex>
 <placeholder>
  <text>#num15</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*5</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>
<answers>
 <partindex>
  <text>4</text>
 </partindex>
 <placeholder>
  <text>#num16</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*6</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>
<answers>
 <partindex>
  <text>5</text>
 </partindex>
 <placeholder>
  <text>#num17</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*7</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>
<answers>
 <partindex>
  <text>6</text>
 </partindex>
 <placeholder>
  <text>#num18</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*8</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>
<answers>
 <partindex>
  <text>7</text>
 </partindex>
 <placeholder>
  <text>#num19</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*9</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>
<answers>
 <partindex>
  <text>8</text>
 </partindex>
 <placeholder>
  <text>#num110</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number1*10</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>
<answers>
 <partindex>
  <text>9</text>
 </partindex>
 <placeholder>
  <text>#num22</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number2*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></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>10</text>
 </partindex>
 <placeholder>
  <text>#num23</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number2*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></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>11</text>
 </partindex>
 <placeholder>
  <text>#num24</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number2*4</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
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 <ruleid>
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 <otherrule>
  <text></text>
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 <subqtext format="html">
<text></text>
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<text></text>
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 <correctfeedback format="html">
<text></text>
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 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
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</answers>
<answers>
 <partindex>
  <text>12</text>
 </partindex>
 <placeholder>
  <text>#num25</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number2*5</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>
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<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>13</text>
 </partindex>
 <placeholder>
  <text>#num26</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
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 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number2*6</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>
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 <subqtext format="html">
<text></text>
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<text></text>
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 <correctfeedback format="html">
<text></text>
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 <partiallycorrectfeedback format="html">
<text></text>
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 <incorrectfeedback format="html">
<text></text>
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</answers>
<answers>
 <partindex>
  <text>14</text>
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 <placeholder>
  <text>#num27</text>
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 <answermark>
  <text>1</text>
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  <text>0</text>
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  <text>1</text>
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 <answer>
  <text>number2*7</text>
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  <text></text>
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 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
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  <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>
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 <incorrectfeedback format="html">
<text></text>
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</answers>
<answers>
 <partindex>
  <text>15</text>
 </partindex>
 <placeholder>
  <text>#num28</text>
 </placeholder>
 <answermark>
  <text>1</text>
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 <answertype>
  <text>0</text>
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 <numbox>
  <text>1</text>
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 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number2*8</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>
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 <otherrule>
  <text></text>
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 <subqtext format="html">
<text></text>
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<text></text>
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 <correctfeedback format="html">
<text></text>
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<text></text>
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 <incorrectfeedback format="html">
<text></text>
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</answers>
<answers>
 <partindex>
  <text>16</text>
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 <placeholder>
  <text>#num29</text>
 </placeholder>
 <answermark>
  <text>1</text>
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 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
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 <vars1>
  <text></text>
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 <answer>
  <text>number2*9</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>
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 <subqtext format="html">
<text></text>
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</answers>
<answers>
 <partindex>
  <text>17</text>
 </partindex>
 <placeholder>
  <text>#num210</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>number2*10</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
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 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext 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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 <incorrectfeedback format="html">
<text></text>
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</answers>
<answers>
 <partindex>
  <text>18</text>
 </partindex>
 <placeholder>
  <text>#least</text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>least</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>
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<text></text>
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 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358788  -->
  <question type="formulas">
    <name>
      <text>TL34 - Multiples- LCM (initials)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What is the LCM of {number1} and {number2}?</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>numbers=shuffle([2:11]);</text>
</varsrandom>
<varsglobal><text><![CDATA[number1=numbers[0];
number2=numbers[1];
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>"));

}]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
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  <text></text>
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  <text>1</text>
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  <text>1</text>
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  <text></text>
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 <answer>
  <text>least</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
 </unitpenalty>
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  <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;">The least common multiple of {number1} and {number2} is <strong>{least}</strong></p><p dir="ltr" style="text-align: left;">The multiples of {number1} are: {multiples1}</p><p dir="ltr" style="text-align: left;">The multiples of {number2} are: {multiples2}</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358793  -->
  <question type="shortanswer">
    <name>
      <text>M5- TL34- Number06- LCM means L___ C___ M__</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><strong><span class="" style="color: rgb(239, 69, 64);">6.&nbsp; </span></strong>LCM means</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><img src="@@PLUGINFILE@@/image.png" alt="" role="presentation" class="img-fluid"></p><p dir="ltr" style="text-align: left;"><a href="https://thecoopcoach.com/mathcourse/L3401_Number06.mp4">L34 Number 06</a><br></p>]]></text>
<file name="image.png" path="/" 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</file>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <usecase>0</usecase>
    <answer fraction="100" format="moodle_auto_format">
      <text>least common multiple</text>
      <feedback format="html">
        <text></text>
      </feedback>
    </answer>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #5/L35 - Line Plots</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 358800  -->
  <question type="formulas">
    <name>
      <text>L35-Line Plots-Test scores 0-100 by 10</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The line plot represents the class grades on a {test} test.
Use the graph to answer the following questions.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1*(.1*{dataMax}),2,{dataMax}+.10*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=({dataMax}/{divisions}); i++) {
    for (let j=0; j&lt;p[i]; j++){
    board.create('text', [ i*{divisions} , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle'});
    }
    }

    board.update();

</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</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[Freq0={1:6:1};
Freq1={1:6:1};
Freq2={1:6:1};
Freq3={1:6:1};
Freq4={1:6:1};
Freq5={1:6:1};
Freq6={1:6:1};
Freq7={1:6:1};
Freq8={1:6:1};
Freq9={1:6:1};
Freq10={1:6:1};
randomQues=shuffle([0:11]);
test={"history","math","science","art","music","physical education","language","grammar","statistics","geometry","arithmetic","polynomial"};]]></text>
</varsrandom>
<varsglobal><text>values=[0,10,20,30,40,50,60,70,80,90,100];
freq=[Freq0,Freq1,Freq2,Freq3,Freq4,Freq5,Freq6,Freq7,Freq8,Freq9,Freq10];
dataMax=100;
divisions=10;
ticks=9;

score1=values[randomQues[0]];
ans1=freq[randomQues[0]];

score2=values[randomQues[1]];
ans2=freq[randomQues[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>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans1</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[How many students scored a {score1}?<br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[There are {ans1} student grades with a score of {score1}.
The grades of {score1} are graphed in <span class="" style="color: rgb(239, 69, 64);">red</span>.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1*(.1*{dataMax}),2,{dataMax}+.10*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=({dataMax}/{divisions}); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {score1}/{divisions}) { board.create('text', [ i*{divisions} , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'red'});
    } else {
    board.create('text', [ i*{divisions} , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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>ans2</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;"></p><h3></h3>How many students scored a {score2}?<br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[There are {ans2} student grades with a score of {score2}.
The grades of {score2} are graphed in <span class="" style="color: rgb(51, 102, 255);">blue</span>.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1*(.1*{dataMax}),2,{dataMax}+.10*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=({dataMax}/{divisions}); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {score2}/{divisions}) { board.create('text', [ i*{divisions} , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'blue'});
    } else {
    board.create('text', [ i*{divisions} , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sum(freq)</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>How many students are in the class (assuming all students took the test)?</text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Each "x" on the board represents a student test.&nbsp; &nbsp;Find the sum of the x's on the graph.</p>
<p>Add the frequency of each score:</p>
<table>
    <tbody>
        <tr>
          <td style="text-align: center;">Score</td><td style="text-align: center;">&nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td style="text-align: center;">Frequency</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[0]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[0]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[1]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[1]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[2]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[2]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[3]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[3]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[4]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[4]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[5]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[5]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[6]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[6]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[7]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[7]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[8]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[8]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[9]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[9]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[10]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[10]}</td>
        </tr>
    </tbody>
</table>
{Freq0}+{Freq1}+{Freq2}+{Freq3}+{Freq4}+{Freq5}+{Freq6}+{Freq7}+{Freq8}+{Freq9}+{Freq10} = {=sum(freq)}]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358801  -->
  <question type="formulas">
    <name>
      <text>L35-Line Plots-Test scores 0-100 by 5</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The line plot represents the class grades on a {test} test.
Use the graph to answer the following questions.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1*(.1*{dataMax}),2,{dataMax}+.10*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=({dataMax}/{divisions}+50); i++) {
    for (let j=0; j&lt;p[i]; j++){
    board.create('text', [ i*{divisions}+50 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle'});
    }
    }

    board.update();

</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</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[Freq0={1:6:1};
Freq1={1:6:1};
Freq2={1:6:1};
Freq3={1:6:1};
Freq4={1:6:1};
Freq5={1:6:1};
Freq6={1:6:1};
Freq7={1:6:1};
Freq8={1:6:1};
Freq9={1:6:1};
Freq10={1:6:1};
randomQues=shuffle([0:11]);
test={"history","math","science","art","music","physical education","language","grammar","statistics","geometry","arithmetic","polynomial"};]]></text>
</varsrandom>
<varsglobal><text>values=[50,55,60,65,70,75,80,85,90,95,100];
freq=[Freq0,Freq1,Freq2,Freq3,Freq4,Freq5,Freq6,Freq7,Freq8,Freq9,Freq10];
dataMax=100;
divisions=5;
ticks=9;

score1=values[randomQues[0]];
ans1=freq[randomQues[0]];
scoreG1=randomQues[0];
score2=values[randomQues[1]];
ans2=freq[randomQues[1]];
scoreG2=randomQues[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>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans1</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[How many students scored a {score1}?<br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[There are {ans1} student grades with a score of {score1}.
The grades of {score1} are graphed in <span class="" style="color: rgb(239, 69, 64);">red</span>.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1*(.1*{dataMax}),2,{dataMax}+.10*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=({dataMax}/{divisions}+50); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {scoreG1}) { board.create('text', [ i*{divisions}+50 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'red'});
    } else {
    board.create('text', [ i*{divisions}+50 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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>ans2</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;"></p><h3></h3>How many students scored a {score2}?<br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[There are {ans2} student grades with a score of {score2}.
The grades of {score2} are graphed in <span class="" style="color: rgb(51, 102, 255);">blue</span>.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1*(.1*{dataMax}),2,{dataMax}+.10*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=({dataMax}/{divisions}+50); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {scoreG2}) { board.create('text', [ i*{divisions}+50 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'blue'});
    } else {
    board.create('text', [ i*{divisions}+50 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sum(freq)</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>How many students are in the class (assuming all students took the test)?</text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Each "x" on the board represents a student test.&nbsp; &nbsp;Find the sum of the x's on the graph.</p>
<p>Add the frequency of each score:</p>
<table>
    <tbody>
        <tr>
          <td style="text-align: center;">Score</td><td style="text-align: center;">&nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td style="text-align: center;">Frequency</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[0]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[0]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[1]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[1]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[2]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[2]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[3]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[3]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[4]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[4]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[5]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[5]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[6]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[6]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[7]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[7]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[8]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[8]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[9]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[9]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[10]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[10]}</td>
        </tr>
    </tbody>
</table>
{Freq0}+{Freq1}+{Freq2}+{Freq3}+{Freq4}+{Freq5}+{Freq6}+{Freq7}+{Freq8}+{Freq9}+{Freq10} = {=sum(freq)}]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358802  -->
  <question type="formulas">
    <name>
      <text>L35-Line Plots-trial other numbers</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The line plot represents the {test}.
Use the graph to answer the following questions.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[10*(.05*{dataMax}),2,2+{dataMax}+.05*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[-5, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: true,drawZero: false,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=(11); i++) {
    for (let j=0; j&lt;p[i]; j++){
    board.create('text', [ i*2+25 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle'});
    }
    }

    board.update();

</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</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>Freq0={0:6:1};
Freq1={0:6:1};
Freq2={0:6:1};
Freq3={0:6:1};
Freq4={0:6:1};
Freq5={0:6:1};
Freq6={0:6:1};
Freq7={0:6:1};
Freq8={0:6:1};
Freq9={0:6:1};
Freq10={0:6:1};
randomQues=shuffle([1:10]);
randomNums=shuffle([25:44]);
randomScenario={0,1,2};</text>
</varsrandom>
<varsglobal><text><![CDATA[values=[25,27,29,31,33,35,37,39,41,43,45];
freq=[Freq0,Freq1,Freq2,Freq3,Freq4,Freq5,Freq6,Freq7,Freq8,Freq9,Freq10];
dataMax=45;
divisions=3;
ticks=4;
scoreG1=randomQues[0];
score1=values[randomQues[0]];
ans1=freq[randomQues[0]];
scoreG2=randomQues[1];
score2=values[randomQues[1]];
ans2=freq[randomQues[1]];
testA=["number of ounces of water dispensed from the water fountain each hour","cost of a pair of sneakers","cost of a jacket at different clothing stores"];
wordA=[join("","How many times was ",score1," ounces dispensed?"),join("","How many pairs of sneakers cost $",score1,"?"),join("","How many stores sold the jacket for $",score1,"?")];
wordB=[join("","How many times was ",score2," ounces dispensed?"),join("","How many pairs of sneakers cost $",score2,"?"),join("","How many stores sold the jacket for $",score2,"?")];
test=testA[randomScenario];
wordP1=wordA[randomScenario];
wordP2=wordB[randomScenario];
recording=["hours","pairs of sneakers","stores"];
record=recording[randomScenario];]]></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>ans1</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[{wordP1}<br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[{score1} {record} is shown in red.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[10*(.05*{dataMax}),2,2+{dataMax}+.05*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[-5, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: true,drawZero: false,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=(11); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {scoreG1}) { board.create('text', [ i*2+25 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'red'});
    } else {
    board.create('text', [ i*2+25 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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>ans2</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;"></p><h3></h3>{wordP2}<br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[{score2} {record} is shown in blue.
<jsxgraph width="450" height="100">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[10*(.05*{dataMax}),2,2+{dataMax}+.05*{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[-5, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: true,drawZero: false,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=(11); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {scoreG2}) { board.create('text', [ i*2+25 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'blue'});
    } else {
    board.create('text', [ i*2+25 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sum(freq)</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>How many {record} are represented in the line plot?</text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Each "x" on the board represents a {record}.&nbsp; &nbsp;Find the sum of the x's on the graph.</p>
<p>Add the frequency of each {record}:</p>
<table>
    <tbody>
        <tr>
          <td style="text-align: center;">{record}</td><td style="text-align: center;">&nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td style="text-align: center;">Frequency</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[0]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[0]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[1]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[1]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[2]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[2]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[3]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[3]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[4]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[4]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[5]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[5]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[6]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[6]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[7]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[7]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[8]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[8]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[9]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[9]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[10]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[10]}</td>
        </tr>
    </tbody>
</table>
{Freq0}+{Freq1}+{Freq2}+{Freq3}+{Freq4}+{Freq5}+{Freq6}+{Freq7}+{Freq8}+{Freq9}+{Freq10} = {=sum(freq)}]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358803  -->
  <question type="formulas">
    <name>
      <text>L35-Line Plots-trial other numbers (Dice)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[The line plot represents the results from rolling two die and recording the sum.
Use the graph to answer the following questions.
<jsxgraph width="450" height="200">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[1,3,{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: true,drawZero: false,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=(10); i++) {
    for (let j=0; j&lt;p[i]; j++){
    board.create('text', [ i+2 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle'});
    }
    }

    board.update();

</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</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>Freq0={0:8:1};
Freq1={0:8:1};
Freq2={0:8:1};
Freq3={0:8:1};
Freq4={0:8:1};
Freq5={0:8:1};
Freq6={0:8:1};
Freq7={0:8:1};
Freq8={0:8:1};
Freq9={0:8:1};
Freq10={0:8:1};
randomQues=shuffle([0:11]);
randomNums=shuffle([0:11]);</text>
</varsrandom>
<varsglobal><text>values=[2,3,4,5,6,7,8,9,10,11,12];
freq=[Freq0,Freq1,Freq2,Freq3,Freq4,Freq5,Freq6,Freq7,Freq8,Freq9,Freq10];
dataMax=13;
divisions=1;
ticks=0;
scoreG1=randomQues[0];
score1=values[randomQues[0]];
ans1=freq[randomQues[0]];
scoreG2=randomQues[1];
score2=values[randomQues[1]];
ans2=freq[randomQues[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>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans1</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[How many times was the sum {score1} rolled?<br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[{score1} was rolled {ans1} times. The data is represented in red on the line plot.
<jsxgraph width="450" height="200">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[1,3,{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: true,drawZero: false,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=(10); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {scoreG1}) { board.create('text', [ i+2 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'red'});
    } else {
    board.create('text', [ i+2 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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>ans2</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;"></p><h3></h3>How many times was the sum {score2} rolled?<br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[{score2} was rolled {ans2} times. The data is represented in red on the line plot.
<jsxgraph width="450" height="200">var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[1,3,{dataMax},-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: true,drawZero: false,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [3, 1],ticksDistance: 10,strokeColor: '#121212',label: {offset: [-5, -10]}}});

    let p = [];
    p.push({Freq0});
    p.push({Freq1});
    p.push({Freq2});
    p.push({Freq3});
    p.push({Freq4});
    p.push({Freq5});
    p.push({Freq6});
    p.push({Freq7});
    p.push({Freq8});
    p.push({Freq9});
    p.push({Freq10});


    for (let i=0; i&lt;=(10); i++) {
    for (let j=0; j&lt;p[i]; j++){
    if (i === {scoreG2}) { board.create('text', [ i+2 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'blue'});
    } else {
    board.create('text', [ i+2 , .3*j+.2,"x"],{fixed:true, showInfobox:false, anchorX:'middle',color:'black'});
    }
    }
    }

    board.update();

</jsxgraph>]]></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></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sum(freq)</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>How many dice rolls are recorded on the line plot?</text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Each "x" on the board represents a {record}.&nbsp; &nbsp;Find the sum of the x's on the graph.</p>
<p>Add the frequency of each dice roll.</p>
<table>
    <tbody>
        <tr>
          <td style="text-align: center;">dice roll</td><td style="text-align: center;">&nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td style="text-align: center;">Frequency</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[0]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[0]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[1]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[1]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[2]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[2]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[3]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[3]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[4]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[4]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[5]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[5]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[6]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[6]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[7]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[7]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[8]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[8]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[9]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[9]}</td>
        </tr>
        <tr>
            <td style="text-align: center;">{values[10]}</td><td style="text-align: center;"></td>
            <td style="text-align: center;">{freq[10]}</td>
        </tr>
    </tbody>
</table>
{Freq0}+{Freq1}+{Freq2}+{Freq3}+{Freq4}+{Freq5}+{Freq6}+{Freq7}+{Freq8}+{Freq9}+{Freq10} = {=sum(freq)}]]></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 #5/L36- Fractions estimation- Improper and Mixed Numbers</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 358812  -->
  <question type="formulas">
    <name>
      <text>fractions- Number Line - estimation</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="500" height="100">
    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,2,2.5,-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});

    var p1=board.create('point',[{point},0],{fixed:true,showInfobox:false,name:"{name}"});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="500" height="100">

    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,2,2.5,-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});

    var p1=board.create('point',[{point},0],{fixed:true,showInfobox:false,name:"{name}"});


    board.create('text', [ {point} , -.8,"{redNum}"], {anchorX:'middle',anchorY:'bottom',strokeColor:'blue'} );
    board.create('line',[[{point}-.05,-.8],[{point}+.05,-.8]],{fixed:true,straightFirst:false,straightLast:false});
    board.create('text', [ {point} , -.8,"{redDen}"], {anchorX:'middle',anchorY:'top',strokeColor:'blue'} );
</jsxgraph>


<h3>There are {den} equal sections between 0 and 1.<br></h3>
<h3>The point is at tick mark {num}.<br>Point {name} is at \(\frac{{num}}{{den}}\)</h3><h3><span><strong>Always </strong><span style="">write fractions in simplest form.&nbsp;&nbsp;<h3>The GCF of {num} and {den} is {GCFFrac}</h3><p>The fraction in simplest form is:&nbsp;<span style="font-size: 1.64062rem;">\(\frac{{redNum}}{{redDen}}\)</span></p></span></span></h3>]]></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[fraction={[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]};
name={"A","B","C","D","E","F","G","H","X","Y","Z"};
number1={1:11:1};
number2={1:11:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number1=(number1==number2)?number1+1:number1;
fraction=sort([number1,number2]);
num=fraction[0];
den=fraction[1];
ticks=den-1;
point=num/den;
whole=(point<.5)?0:1;
GCFFrac=gcd(num,den);
redNum=num/GCFFrac;
redDen=den/GCFFrac;]]></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>[num,den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0/_1 == num/den)*.5 + (_0==redNum)*.25 + (_1==redDen)*.25</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">
                <h3>What fraction is point {name}?&nbsp;</h3><h5>(Enter the fraction in simplest terms)&nbsp;</h5>
            </td>
            <td style="border-bottom:1px solid black"><h3>{_0}</h3></td>
      </tr><tr> <td><h3>{_1}
            </h3></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>
<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>whole</text>
 </answer>
 <vars2>
  <text><![CDATA[FB=pick(point<.5,"The point is greater than a half, round up" ,"The point is less than a half, round down") ;]]></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;"></p><h3>Round point {name} to the nearest whole number. {_0}&nbsp;</h3><br><p></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: 358810  -->
  <question type="formulas">
    <name>
      <text>L36 - improper fraction to mixed number</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Write the improper fraction \(\frac{{impNum}}{{denominator}}\) as a mixed number in simplest form.</p><p dir="ltr" style="text-align: left;">(If the answer is a whole number use a "0" in the numerator)</p><p dir="ltr" style="text-align: left;"><br></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>num=shuffle([2:21]);</text>
</varsrandom>
<varsglobal><text><![CDATA[#assign numerator to larger number
impNum=(num[0]>num[1])?num[0]:num[1];

#assign denominator to smaller number
denominator=(num[0]>num[1])?num[1]:num[0];

wholeNum=floor(impNum/denominator);
mixNum=impNum%denominator;

GCFFrac=gcd(mixNum,denominator);
redNum=mixNum/GCFFrac;
redDen=denominator/GCFFrac;
]]></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><![CDATA[FB=pick(GCFFrac>1,"",join(""," = ",wholeNum,"\\(\\frac{",redNum,"}{",redDen,"}\\)"));]]></text>
 </vars1>
 <answer>
  <text>[wholeNum,redNum,redDen]</text>
 </answer>
 <vars2>
  <text><![CDATA[crit1=(_0==wholeNum)*.3;
crit2=((_1/_2) == (redNum/redDen))*.2;
crit3=((_1==redNum) && (_2==redDen))*.5;]]></text>
 </vars2>
 <correctness>
  <text>crit1+crit2+crit3</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"> {_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><![CDATA[<p dir="ltr" style="text-align: left;">&nbsp;\(\frac{{impNum}}{{denominator}}\)={wholeNum}\(\frac{{mixNum}}{{denominator}}\) {FB}</p>
<p dir="ltr" style="text-align: left;"><br></p>
<p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(255, 51, 102);">{impNum}</span>&nbsp;÷ <span class="" style="color: rgb(51, 102, 255);">{denominator} </span>= <span class="" style="color: rgb(245, 184, 0);">{wholeNum}&nbsp;</span></p>
<p dir="ltr" style="text-align: left;">How many are left over?&nbsp; &nbsp;<span class="" style="color: rgb(152, 202, 62);">{mixNum}</span> left over</p>
<table>
    <tbody>
        <tr>
            <td>
            </td>
            <td><span class="" style="color: rgb(245, 184, 0);">{wholeNum}</span>
            </td>
            <td>&nbsp;remainder <span class="" style="color: rgb(152, 202, 62);">{mixNum}</span></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(51, 102, 255);">{denominator}</span></td>
            <td style="border-top: 1px solid black; border-left:1px solid black"><span class="" style="color: rgb(255, 51, 102);">{impNum}</span></td>
            <td></td>
        </tr>
    </tbody>
</table><br><strong>Reduce the fraction when necessary.</strong>&nbsp; &nbsp;&nbsp;{wholeNum}\(\frac{{mixNum}}{{denominator}}\)<br>The Greatest Common Factor (GCF) of the numerator and denominator = {GCFFrac}<br><br>{mixNum}&nbsp;÷ {GCFFrac} = {redNum}<br>{denominator}&nbsp;÷ {GCFFrac} = {redDen}<br><br>The answer in simplest form is&nbsp; {wholeNum}\(\frac{{redNum}}{{redDen}}\)<br><br><br><br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358811  -->
  <question type="formulas">
    <name>
      <text>L36 -mixed number to improper fraction</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Write the mixed number&nbsp;{wholeNum}\(\frac{{redNum}}{{redDen}}\) as an improper fraction.</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>num=shuffle([2:21]);</text>
</varsrandom>
<varsglobal><text><![CDATA[#assign numerator to larger number
impNum=(num[0]>num[1])?num[0]:num[1];

#assign denominator to smaller number
denominator=(num[0]>num[1])?num[1]:num[0];

wholeNum=floor(impNum/denominator);
mixNum=impNum%denominator;

GCFFrac=gcd(mixNum,denominator);
redNum=mixNum/GCFFrac;
redDen=denominator/GCFFrac;
impNum=redDen*wholeNum + redNum;
impDen=redDen;
]]></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>[impNum,impDen]</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[<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;">{wholeNum}\(\frac{{redNum}}{{redDen}}\) = \(\frac{{impNum}}{{impDen}}\)</p>
<p dir="ltr" style="text-align: left;"><br></p>
<table>
    <tbody>
        <tr>
            <td rowspan="2" style="text-align: right;"><span class="" style="color: rgb(51, 102, 255);">{wholeNum}</span></td>
            <td style="border-bottom:1px solid black"><span class="" style="color: rgb(152, 202, 62);">+ {redNum}</span></td>
            <td rowspan="2" style="text-align: center;">=</td>
            <td style="text-align: center; border-bottom: 1px solid black;"><span class="" style="color: rgb(204, 51, 255);">{impNum}</span></td>
        </tr>
        <tr>
            <td><span class="" style="color: rgb(255, 51, 102);">• {redDen}</span></td>
            <td style="text-align: center;"><span class="" style="color: rgb(255, 51, 102);">{impDen}</span></td>
        </tr>
    </tbody>
</table>
<p dir="ltr" style="text-align: left;">Multiply the denominator by the whole number:&nbsp; &nbsp;<span class="" style="color: rgb(255, 51, 102);">{redDen}</span><span style="font-size: 0.9375rem;">&nbsp;</span>• <span class="" style=" color: rgb(51, 102, 255);">{wholeNum} </span><span style="font-size: 0.9375rem;">= </span><span class="" style=" color: rgb(245, 184, 0);">{=wholeNum*redDen}</span></p>
<div class="editor-indent" style="margin-left: 30px;"><p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(245, 184, 0);"><span class="" style="color: rgb(51, 51, 51);">Add the numerator to the product:</span>&nbsp;&nbsp;<span>&nbsp;</span><span>{=wholeNum*redDen} + <span class="" style="color: rgb(152, 202, 62);">{redNum} <span class="" style="color: rgb(204, 51, 255);">= {impNum}</span></span></span></span></p></div>
<p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(245, 184, 0);"><span><span class="" style="color: rgb(152, 202, 62);"><span class="" style="color: rgb(204, 51, 255);"><span class="" style="color: rgb(51, 51, 51);">Keep the same denominator:&nbsp;</span> <span class="" style="color: rgb(255, 51, 102);">{impDen}</span></span></span></span></span></p>
<p dir="ltr" style="text-align: left;"></p><br><br>&nbsp;{wholeNum}\(\frac{{redNum}}{{redDen}}\) =&nbsp;\(\frac{{impNum}}{{impDen}}\)<br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358815  -->
  <question type="formulas">
    <name>
      <text>L36- fractions- Number Line - estimation</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="500" height="100">
    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,2,2.5,-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});

    var p1=board.create('point',[{point},0],{fixed:true,showInfobox:false,name:"{name}"});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="500" height="100">

    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,2,2.5,-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});

    var p1=board.create('point',[{point},0],{fixed:true,showInfobox:false,name:"{name}"});


    board.create('text', [ {point} , -.8,"{redNum}"], {anchorX:'middle',anchorY:'bottom',strokeColor:'blue'} );
    board.create('line',[[{point}-.05,-.8],[{point}+.05,-.8]],{fixed:true,straightFirst:false,straightLast:false});
    board.create('text', [ {point} , -.8,"{redDen}"], {anchorX:'middle',anchorY:'top',strokeColor:'blue'} );
</jsxgraph>


<h3>There are {den} equal sections between 0 and 1.<br></h3>
<h3>The point is at tick mark {num}.<br>Point {name} is at \(\frac{{num}}{{den}}\)</h3><h3><span><strong>Always </strong><span style="">write fractions in simplest form.&nbsp;&nbsp;<h3>The GCF of {num} and {den} is {GCFFrac}</h3><p>The fraction in simplest form is:&nbsp;<span style="font-size: 1.64062rem;">\(\frac{{redNum}}{{redDen}}\)</span></p></span></span></h3>]]></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[fraction={[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]};
name={"A","B","C","D","E","F","G","H","X","Y","Z"};
number1={1:11:1};
number2={1:11:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number1=(number1==number2)?number1+1:number1;
fraction=sort([number1,number2]);
num=fraction[0];
den=fraction[1];
ticks=den-1;
point=num/den;
whole=(point<.5)?0:1;
GCFFrac=gcd(num,den);
redNum=num/GCFFrac;
redDen=den/GCFFrac;]]></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>[num,den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0/_1 == num/den)*.5 + (_0==redNum)*.25 + (_1==redDen)*.25</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">
                <h3>What fraction is point {name}?&nbsp;</h3><h5>(Enter the fraction in simplest terms)&nbsp;</h5>
            </td>
            <td style="border-bottom:1px solid black"><h3>{_0}</h3></td>
      </tr><tr> <td><h3>{_1}
            </h3></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>
<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>whole</text>
 </answer>
 <vars2>
  <text><![CDATA[FB=pick(point<.5,"The point is greater than a half, round up" ,"The point is less than a half, round down") ;]]></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;"></p><h3>Round point {name} to the nearest whole number. {_0}&nbsp;</h3><br><p></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: 358817  -->
  <question type="formulas">
    <name>
      <text>L36- fractions- Number Line - estimation (whole number)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="400" height="100">
    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,2,{wholeNum}+1.5,-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});

    var p1=board.create('point',[{point},0],{fixed:true,showInfobox:false,name:"{name}",size:1});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<jsxgraph width="400" height="100">

    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1,2,{wholeNum}+1.5,-2], axis:false, ShowCopyright: false, showNavigation:false});

    var numLine = board.create('axis', [[0, 0],[5, 0]], {firstArrow: true,lastArrow: true,ticks: {insertTicks: false,drawZero: true,majorHeight: 4,minorHeight: 2,minorTicks: {ticks},tickEndings: [5, 6],ticksDistance: 1,strokeColor: '#121212',label: {offset: [-.5, -20]}}});

    var p1=board.create('point',[{point},0],{fixed:true,showInfobox:false,name:"{name}",size:1});

    board.create('text',[{point}-.05,-0.8,"{wholeNum}"],{anchorX:'right',anchorY:'middle',strokeColor:'blue',fontsize:'30'});
    board.create('text', [ {point} , -.8,"{redNum}"], {anchorX:'middle',anchorY:'bottom',strokeColor:'blue'} );
    board.create('line',[[{point}-.05,-.8],[{point}+.05,-.8]],{fixed:true,straightFirst:false,straightLast:false});
    board.create('text', [ {point} , -.8,"{redDen}"], {anchorX:'middle',anchorY:'top',strokeColor:'blue'} );
</jsxgraph>


<h3>There are {den} equal sections between 0 and 1.<br></h3>
<h3>The point is at tick mark {num}.<br>Point {name} is at \(\frac{{num}}{{den}}\)</h3>
<h3><span><strong>Always </strong><span style="">write fractions in simplest form.&nbsp;&nbsp;<h3>The GCF of {num} and {den} is {GCFFrac}</h3>
            <p>The fraction in simplest form is:&nbsp;<span style="font-size: 1.64062rem;">\(\frac{{redNum}}{{redDen}}\)</span></p><p><span style="font-size: 1.64062rem;"><br></span></p><p><span style="font-size: 1.64062rem;">The fraction is to the right of {wholeNum}, therefore the point is at {wholeNum}\(\frac{{redNum}}{{redDen}}\)</span></p><p><span style="font-size: 1.64062rem;"><br></span></p><p><span style="font-size: 1.64062rem;">Round to the nearest whole number:</span></p><p><span style="font-size: 1.64062rem;">\(\frac{{redNum}}{{redDen}}\)&nbsp;</span><span style="font-size: 1.64062rem;">{FBfrac}</span></p>
        </span></span></h3>]]></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[fraction={[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]};
name={"A","B","C","D","E","F","G","H","X","Y","Z"};
number1={1:11:1};
number2={1:11:1};
wholeNum={1:8:1}]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number1=(number1==number2)?number1+1:number1;
fraction=sort([number1,number2]);
num=fraction[0];
den=fraction[1];
ticks=den-1;
point=wholeNum+num/den;
whole=(point<(wholeNum+.5))?wholeNum:wholeNum+1;
GCFFrac=gcd(num,den);
redNum=num/GCFFrac;
redDen=den/GCFFrac;
FBfrac=pick(point<(wholeNum+.5),join(""," is equal to or greater than one half, round up to ",wholeNum+1),join(""," is less than one half, therefore round down to ",wholeNum));]]></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>[num,den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0/_1 == num/den)*.5 + (_0==redNum)*.25 + (_1==redDen)*.25</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">
                <h3>What fraction is point {name}?&nbsp;</h3>
                <h3>(Enter the fraction in simplest terms)&nbsp;</h3>
            </td>
            <td rowspan="2"><h3>&nbsp; &nbsp; &nbsp; {wholeNum}</h3></td>
            <td style="border-bottom:1px solid black">
                <h3>{_0}</h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{_1}
                </h3>
            </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>
<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>whole</text>
 </answer>
 <vars2>
  <text><![CDATA[FB=pick(point<.5,"The point is greater than a half, round up" ,"The point is less than a half, round down") ;]]></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;"></p><h3>Round point {name} to the nearest whole number. {_0}&nbsp;</h3><br><p></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: 358813  -->
  <question type="formulas">
    <name>
      <text>L36- mixed number with eighths</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="{width}" height="150">
    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1.5,1.5,1.5*({whole}+2),-1.5], axis:false, ShowCopyright: false, showNavigation:false});


    var s1 = board.create('sector', [[0,0], [1, 0], [{x1},{y1}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s1Fill}', strokeColor: 'black'});

    var s2 = board.create('sector', [[0,0], [{x1},{y1}], [{x2},{y2}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s2Fill}', strokeColor: 'black'});

    var s3 = board.create('sector', [[0,0], [{x2},{y2}], [{x3},{y3}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s3Fill}', strokeColor: 'black'});

    var s4 = board.create('sector', [[0,0], [{x3},{y3}], [{x4},{y4}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s4Fill}', strokeColor: 'black'});

    var s5 = board.create('sector', [[0,0], [{x4},{y4}], [{x5},{y5}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s5Fill}', strokeColor: 'black'});

    var s6 = board.create('sector', [[0,0], [{x5},{y5}], [{x6},{y6}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s6Fill}', strokeColor: 'black'});

    var s7 = board.create('sector', [[0,0], [{x6},{y6}], [{x7},{y7}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s7Fill}', strokeColor: 'black'});

    var s8 = board.create('sector', [[0,0], [{x7},{y7}], [1,0]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s8Fill}', strokeColor: 'black'});



    for (let i=0; i&lt;{whole}; i++) {
    board.create('circle', [[2.5+(2.5*i), 0],[3.5+(2.5*i),0]],{strokeColor:'black',fillColor:'{shadeColor}'} );
    }



</jsxgraph>]]></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[num={1,2,3,4,5,6,7};
colors=shuffle(["green","red","brown","purple","pink","blue","orange"]);
whole={1,2};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[width=150*(whole+1);
den=8;
ansNum=den*whole+num;
GCFFrac=gcd(ansNum,den);
redNum=ansNum/GCFFrac;
redDen=den/GCFFrac;
FBWhole=pick(whole==1,"There are 2 circles shaded","There is 1 circle shaded");
x1=cos(deg2rad(45));
y1=sin(deg2rad(45));
x2=0;
y2=1;
x3=-1*cos(deg2rad(45));
y3=sin(deg2rad(45));
x4=-1;
y4=0;
x5=-1*cos(deg2rad(45));
y5=-1*sin(deg2rad(45));
x6=0;
y6=-1;
x7=cos(deg2rad(45));
y7=-1*sin(deg2rad(45));

fillColor="white";
shadeColor=colors[0];
shadeColor2=colors[1];
s1Fill=pick(1<=num,fillColor,shadeColor);
s2Fill=pick(2<=num,fillColor,shadeColor);
s3Fill=pick(3<=num,fillColor,shadeColor);
s4Fill=pick(4<=num,fillColor,shadeColor);
s5Fill=pick(5<=num,fillColor,shadeColor);
s6Fill=pick(6<=num,fillColor,shadeColor);
s7Fill=pick(7<=num,fillColor,shadeColor);
s8Fill=pick(8<=num,fillColor,shadeColor);]]></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>[ansNum,den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0/_1 == ansNum/den)*.5 +(_0==redNum)*.25 + (_1==redDen)*.25</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[<br><table>
    <tbody>
        <tr>
            <td rowspan="2">
                <h3>What improper fraction represents the amount of circle shaded?&nbsp;</h3>
            </td>
            <td style="border-bottom:1px solid black"><h3>{_0}</h3></td>
      </tr><tr> <td><h3>{_1}
            </h3></td>
        </tr>
    </tbody>
</table><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr"><strong>The circle is divided into eight equal sections.&nbsp; &nbsp;Each section represents \(\frac{1}{8}\).</strong></p><p dir="ltr">There are {num} sections shaded in the left circle.</p><p dir="ltr">{FBWhole}.&nbsp; Each whole circle represents \(\frac{8}{8}\).</p><p dir="ltr">Altogether there are {ansNum} eighths shaded.&nbsp;</p><p dir="ltr">The fraction is \(\frac{{ansNum}}{{den}}\).</p>Write the answer in lowest terms.<br>The GCF of {ansNum} and {den} = {GCFFrac}<br><br>The fraction can be reduced if the GCF is greater than 1.<br>To reduce the fraction divide the numerator and denominator each by the GCF<br><br>{ansNum}/{GCFFrac} = {redNum}<br>{den}/{GCFFrac}={redDen}<br><br><strong>The answer as an improper fraction in simplest form is: \(\frac{{redNum}}{{redDen}}\)</strong><br><br><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>3</text>
 </numbox>
 <vars1>
  <text>gcfFrac=gcd(num,den);
redMNum=num/gcfFrac;
redMDen=den/gcfFrac;</text>
 </vars1>
 <answer>
  <text>[whole,redMNum,redMDen]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0==whole)*.3 + (_1/_2==num/den)*.2+(_1==redMNum)*.25 + (_2==redMDen)*.25</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[<br>
<table>
    <tbody>
        <tr>
            <td rowspan="2">
                <h3>What mixed number represents the part of the shaded circle?&nbsp; &nbsp;&nbsp;</h3>
            </td>
          <td rowspan="2"><h3>
            {_0}</h3></td>
            <td style="border-bottom:1px solid black">
                <h3>{_1}</h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{_2}
                </h3>
            </td>
        </tr>
    </tbody>
</table><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{FBWhole}.<br></p><p dir="ltr" style="text-align: left;">Write the fraction in lowest terms.<br>The GCF of {num} and {den} = {gcfFrac}<br><br>A fraction can be reduced if the GCF is greater than 1.<br>To reduce the fraction divide the numerator and denominator each by the GCF<br><br>{num}/{gcfFrac} = {redMNum}<br>{den}/{gcfFrac}={redMDen}<br><br><strong>The answer as a Mixed Number in simplest form is: {whole}\(\frac{{redMNum}}{{redMDen}}\)</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358816  -->
  <question type="formulas">
    <name>
      <text>L36- mixed number with random 1/2 - 9/10</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<jsxgraph width="{width}" height="150">
    var board = JXG.JSXGraph.initBoard(BOARDID, {boundingbox:[-1.5,1.5,1.5*({whole}+2),-1.5], axis:false, ShowCopyright: false, showNavigation:false});

    board.create('circle', [[0, 0],[1,0]],{strokeColor:'black'});

    var s1 = board.create('sector', [[0,0], [1,0], [{sectX},{sectY}]], {
    anglePoint: {visible:false}, center: {visible: false}, radiusPoint: {visible: false},
    fillColor: '{s1Fill}', strokeColor: 'black'});


    var l1=board.create('line',[[0,0],[{x[0]},{y[0]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l2=board.create('line',[[0,0],[{x[1]},{y[1]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l3=board.create('line',[[0,0],[{x[2]},{y[2]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l4=board.create('line',[[0,0],[{x[3]},{y[3]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l5=board.create('line',[[0,0],[{x[4]},{y[4]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l6=board.create('line',[[0,0],[{x[5]},{y[5]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l7=board.create('line',[[0,0],[{x[6]},{y[6]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l8=board.create('line',[[0,0],[{x[7]},{y[7]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l9=board.create('line',[[0,0],[{x[8]},{y[8]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l10=board.create('line',[[0,0],[{x[9]},{y[9]}]],{strokeColor:'black',straightFirst:false, straightLast:false});
    var l11=board.create('line',[[0,0],[{x[10]},{y[10]}]],{strokeColor:'black',straightFirst:false, straightLast:false});


    for (let i=0; i&lt;{whole}; i++) {
    board.create('circle', [[2.5+(2.5*i), 0],[3.5+(2.5*i),0]],{strokeColor:'black',fillColor:'{shadeColor}'} );
    }



</jsxgraph>]]></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[fraction={[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]};
colors=shuffle(["green","red","brown","purple","black","blue","orange"]);
whole={1,2};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[num=fraction[0];
den=fraction[1];
width=150*(whole+1);
denWord=pick(den,"","","halves","thirds","fourths","fifths","sixths","sevenths","eighths","ninths","tenths");
ansNum=den*whole+num;
GCFFrac=gcd(ansNum,den);
redNum=ansNum/GCFFrac;
redDen=den/GCFFrac;
FBWhole=pick(whole==1,"There are 2 circles shaded","There is 1 circle shaded");
x=fill(11,0);
y=fill(11,0);
sectX=cos(deg2rad(num*360/den));
sectY=sin(deg2rad(num*360/den));

x[0]=cos(deg2rad(360/den));
y[0]=sin(deg2rad(360/den));
x[1]=cos(deg2rad(2*360/den));
y[1]=sin(deg2rad(2*360/den));
x[2]=cos(deg2rad(3*360/den));
y[2]=sin(deg2rad(3*360/den));
x[3]=cos(deg2rad(4*360/den));
y[3]=sin(deg2rad(4*360/den));
x[4]=cos(deg2rad(5*360/den));
y[4]=sin(deg2rad(5*360/den));
x[5]=cos(deg2rad(6*360/den));
y[5]=sin(deg2rad(6*360/den));
x[6]=cos(deg2rad(7*360/den));
y[6]=sin(deg2rad(7*360/den));
x[7]=cos(deg2rad(8*360/den));
y[7]=sin(deg2rad(8*360/den));
x[8]=cos(deg2rad(9*360/den));
y[8]=sin(deg2rad(9*360/den));
x[9]=cos(deg2rad(10*360/den));
y[9]=sin(deg2rad(10*360/den));
x[10]=cos(deg2rad(11*360/den));
y[10]=sin(deg2rad(11*360/den));





fillColor="white";
shadeColor=colors[0];
shadeColor2=colors[1];
s1Fill=pick(1<=num,fillColor,shadeColor);
s2Fill=pick(2<=num,fillColor,shadeColor);
s3Fill=pick(3<=num,fillColor,shadeColor);
s4Fill=pick(4<=num,fillColor,shadeColor);
s5Fill=pick(5<=num,fillColor,shadeColor);
s6Fill=pick(6<=num,fillColor,shadeColor);
s7Fill=pick(7<=num,fillColor,shadeColor);
s8Fill=pick(8<=num,fillColor,shadeColor);]]></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>[ansNum,den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0/_1 == ansNum/den)*.5 +(_0==redNum)*.25 + (_1==redDen)*.25</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[<br><table>
    <tbody>
        <tr>
            <td rowspan="2">
                <h3>What improper fraction represents the amount of circle shaded?&nbsp;</h3>
            </td>
            <td style="border-bottom:1px solid black"><h3>{_0}</h3></td>
      </tr><tr> <td><h3>{_1}
            </h3></td>
        </tr>
    </tbody>
</table><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr"><strong>The circle is divided into eight equal sections.&nbsp; &nbsp;Each section represents \(\frac{1}{{den}}\).</strong></p><p dir="ltr">There are {num} sections shaded in the left circle.</p><p dir="ltr">{FBWhole}.&nbsp; Each whole circle represents \(\frac{{den}}{{den}}\).</p><p dir="ltr">Altogether there are {ansNum}&nbsp; {denWord}&nbsp; shaded.&nbsp;</p><p dir="ltr">The fraction is \(\frac{{ansNum}}{{den}}\).</p>Write the answer in lowest terms.<br>The GCF of {ansNum} and {den} = {GCFFrac}<br><br>The fraction can be reduced if the GCF is greater than 1.<br>To reduce the fraction divide the numerator and denominator each by the GCF<br><br>{ansNum}/{GCFFrac} = {redNum}<br>{den}/{GCFFrac}={redDen}<br><br><strong>The answer as an improper fraction in simplest form is: \(\frac{{redNum}}{{redDen}}\)</strong><br><br><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>3</text>
 </numbox>
 <vars1>
  <text>gcfFrac=gcd(num,den);
redMNum=num/gcfFrac;
redMDen=den/gcfFrac;
whole=(redMDen==redMNum)?whole+1:whole;
redMNum=(redMDen==redMNum)?0:redMNum;</text>
 </vars1>
 <answer>
  <text>[whole,redMNum,redMDen]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0==whole)*.3 + (_1/_2==num/den)*.2+(_1==redMNum)*.25 + (_2==redMDen)*.25</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[<br>
<table>
    <tbody>
        <tr>
            <td rowspan="2">
                <h3>What mixed number represents the part of the shaded circle?&nbsp; &nbsp;&nbsp;</h3>
            </td>
          <td rowspan="2"><h3>
            {_0}</h3></td>
            <td style="border-bottom:1px solid black">
                <h3>{_1}</h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{_2}
                </h3>
            </td>
        </tr>
    </tbody>
</table><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{FBWhole}.<br></p><p dir="ltr" style="text-align: left;">Write the fraction in lowest terms.<br>The GCF of {num} and {den} = {gcfFrac}<br><br>A fraction can be reduced if the GCF is greater than 1.<br>To reduce the fraction divide the numerator and denominator each by the GCF<br><br>{num}/{gcfFrac} = {redMNum}<br>{den}/{gcfFrac}={redMDen}<br><br><strong>The answer as a Mixed Number in simplest form is: {whole}\(\frac{{redMNum}}{{redMDen}}\)</strong><br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358825  -->
  <question type="formulas">
    <name>
      <text>Wendy Harper corrected</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<span class="" style="color: rgb(239, 69, 64);"><strong>16.</strong></span>
<jsxgraph width="{width}" height="150">

    var board = JXG.JSXGraph.initBoard(BOARDID, {
    boundingbox:[-1.5,1.5,1.5+({whole}*2),-1.5],
    axis:false,
    showCopyright: false,
    showNavigation:false,
    keepaspectratio:true
    });

    board.create('circle', [[0, 0], 1],{
    strokeColor:'black',
    fixed:true
    });

    var s1 = board.create('sector', [[0,0], [1,0], [{sectX},{sectY}]], {
    anglePoint: {visible:false},
    center: {visible: false},
    radiusPoint: {visible: false},
    fillColor: '{s1Fill}',
    strokeColor: 'black',
    fixed:true
    });

    let x = [{x_0},{x_1},{x_2},{x_3},{x_4},{x_5},{x_6},{x_7},{x_8},{x_9},{x_10}],
    y = [{y_0},{y_1},{y_2},{y_3},{y_4},{y_5},{y_6},{y_7},{y_8},{y_9},{y_10}];

    let l = [];

    for (let i=0; JXG.Math.leq(i,{den}); i++){
    l.push(
    board.create('line',[[0,0],[x[i],y[i]]],{
    strokeColor:'black',
    straightFirst:false,
    straightLast:false,
    fixed:true
    })
    );
    }

    for (let i=0; JXG.Math.lt(i, {whole}); i++) {
    board.create('circle', [[2.5+(2.5*i), 0], 1], {
    strokeColor:'black',
    fillColor:'{shadeColor}',
    fixed:true
    });
    }

</jsxgraph>]]></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[fraction={[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]};
colors=shuffle(["green","red","brown","purple","black","blue","orange"]);
whole={1,2};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[num=fraction[0];
den=fraction[1];
width=150+(whole*125);
denWord=pick(den,"","","halves","thirds","fourths","fifths","sixths","sevenths","eighths","ninths","tenths");
numberWord=pick(den,"","","two","three","four","five","six","seven","eight","nine","ten");
ansNum=den*whole+num;
GCFFrac=gcd(ansNum,den);
redNum=ansNum/GCFFrac;
redDen=den/GCFFrac;
FBWhole=pick(whole==1,"There are 2 circles shaded","There is 1 circle shaded");
x=fill(11,0);
y=fill(11,0);
sectX=cos(deg2rad(num*360/den));
sectY=sin(deg2rad(num*360/den));

x_0=cos(deg2rad(360/den));
y_0=sin(deg2rad(360/den));
x_1=cos(deg2rad(2*360/den));
y_1=sin(deg2rad(2*360/den));
x_2=cos(deg2rad(3*360/den));
y_2=sin(deg2rad(3*360/den));
x_3=cos(deg2rad(4*360/den));
y_3=sin(deg2rad(4*360/den));
x_4=cos(deg2rad(5*360/den));
y_4=sin(deg2rad(5*360/den));
x_5=cos(deg2rad(6*360/den));
y_5=sin(deg2rad(6*360/den));
x_6=cos(deg2rad(7*360/den));
y_6=sin(deg2rad(7*360/den));
x_7=cos(deg2rad(8*360/den));
y_7=sin(deg2rad(8*360/den));
x_8=cos(deg2rad(9*360/den));
y_8=sin(deg2rad(9*360/den));
x_9=cos(deg2rad(10*360/den));
y_9=sin(deg2rad(10*360/den));
x_10=cos(deg2rad(11*360/den));
y_10=sin(deg2rad(11*360/den));





fillColor="white";
shadeColor=colors[0];
shadeColor2=colors[1];
s1Fill=pick(1<=num,fillColor,shadeColor);
s2Fill=pick(2<=num,fillColor,shadeColor);
s3Fill=pick(3<=num,fillColor,shadeColor);
s4Fill=pick(4<=num,fillColor,shadeColor);
s5Fill=pick(5<=num,fillColor,shadeColor);
s6Fill=pick(6<=num,fillColor,shadeColor);
s7Fill=pick(7<=num,fillColor,shadeColor);
s8Fill=pick(8<=num,fillColor,shadeColor);]]></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>[ansNum,den]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0/_1 == ansNum/den)*.5 +(_0==redNum)*.25 + (_1==redDen)*.25</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[<br><table>
    <tbody>
        <tr>
            <td rowspan="2">
                <h3>What improper fraction represents the amount of circle shaded?&nbsp;</h3>
            </td>
            <td style="border-bottom:1px solid black"><h3>{_0}</h3></td>
      </tr><tr> <td><h3>{_1}
            </h3></td>
        </tr>
    </tbody>
</table><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr"><strong>The circle is divided into {numberWord} equal sections.&nbsp; &nbsp;Each section represents \(\frac{1}{{den}}\).</strong></p><p dir="ltr">There are {num} sections shaded in the left circle.</p><p dir="ltr">{FBWhole}.&nbsp; Each whole circle represents \(\frac{{den}}{{den}}\).</p><p dir="ltr">Altogether there are {ansNum}&nbsp; {denWord}&nbsp; shaded.&nbsp;</p><p dir="ltr">The fraction is \(\frac{{ansNum}}{{den}}\).</p>Write the answer in lowest terms.<br>The GCF of {ansNum} and {den} = {GCFFrac}<br><br>The fraction can be reduced if the GCF is greater than 1.<br>To reduce the fraction divide the numerator and denominator each by the GCF<br><br>{ansNum}/{GCFFrac} = {redNum}<br>{den}/{GCFFrac}={redDen}<br><br><strong>The answer as an improper fraction in simplest form is: \(\frac{{redNum}}{{redDen}}\)</strong><br><br><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>3</text>
 </numbox>
 <vars1>
  <text>gcfFrac=gcd(num,den);
redMNum=num/gcfFrac;
redMDen=den/gcfFrac;
whole=(redMDen==redMNum)?whole+1:whole;
redMNum=(redMDen==redMNum)?0:redMNum;</text>
 </vars1>
 <answer>
  <text>[whole,redMNum,redMDen]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>(_0==whole)*.3 + (_1/_2==num/den)*.2+(_1==redMNum)*.25 + (_2==redMDen)*.25</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[<br>
<table>
    <tbody>
        <tr>
            <td rowspan="2">
                <h3>What mixed number represents the part of the shaded circle?&nbsp; &nbsp;&nbsp;</h3>
            </td>
          <td rowspan="2"><h3>
            {_0}</h3></td>
            <td style="border-bottom:1px solid black">
                <h3>{_1}</h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{_2}
                </h3>
            </td>
        </tr>
    </tbody>
</table><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">{FBWhole}.<br></p><p dir="ltr" style="text-align: left;">Write the fraction in lowest terms.<br>The GCF of {num} and {den} = {gcfFrac}<br><br>A fraction can be reduced if the GCF is greater than 1.<br>To reduce the fraction divide the numerator and denominator each by the GCF<br><br>{num}/{gcfFrac} = {redMNum}<br>{den}/{gcfFrac}={redMDen}<br><br><strong>The answer as a Mixed Number in simplest form is: {whole}\(\frac{{redMNum}}{{redMDen}}\)</strong><br></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 #5/L37 -Multiply Signed Numbers</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 358828  -->
  <question type="formulas">
    <name>
      <text>L37- Multiplying Integers (parentheses)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>0.2500000</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>num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</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[<h3 style="text-align: left;">{A}({B}) = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">{A}({B}) = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><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: 358826  -->
  <question type="formulas">
    <name>
      <text>L37- Multiplying Signed Numbers (4 in one)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</td>
  </tr>
  <tr><td>
    {#b}</td>
  </tr>
  <tr>
    <td>{#c}</td>
      </tr> <tr>
    <td>{#d}</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'
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    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');
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        var ctx = c.getContext("2d");
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        if (actualWidth >= checkWidth) {
            $(".formulas_number").width(actualWidth + sizeN);
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            $(".formulas_number").width(defaultWidth);
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        $(".formulas_number").css("padding-left", "10px");
        newWidth();
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
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    <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>num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>1</text>
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  <text>1</text>
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 <otherrule>
  <text></text>
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 <subqtext format="html">
<text><![CDATA[<h3 style="text-align: left;">{A} • {B} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">{A} • {B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><p></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
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 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
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<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
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 <placeholder>
  <text>#b</text>
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 <answertype>
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  <text>1</text>
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 <vars1>
  <text><![CDATA[a=num1[1];
b=num2[1];
Sa=signA[1];
Sb=signB[1];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
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  <text></text>
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 <ruleid>
  <text>1</text>
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 <otherrule>
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 <subqtext format="html">
<text><![CDATA[<h3></h3><h3>{A}&nbsp;•&nbsp;{B} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span>{A} • {B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
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<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
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</answers>
<answers>
 <partindex>
  <text>2</text>
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 <placeholder>
  <text>#c</text>
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  <text><![CDATA[a=num1[2];
b=num2[2];
Sa=signA[2];
Sb=signB[2];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</text>
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  <text>_err == 0</text>
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<text><![CDATA[<h3>{A} • {B} = {_0}</h3>]]></text>
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<text><![CDATA[<h3></h3><h3><span>{A} • {B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></text>
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<text></text>
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 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>3</text>
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 <placeholder>
  <text>#d</text>
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 <numbox>
  <text>1</text>
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 <vars1>
  <text><![CDATA[a=num1[3];
b=num2[3];
Sa=signA[3];
Sb=signB[3];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</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[<h3></h3><h3>{A}&nbsp;•&nbsp;{B} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span>{A} • {B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358827  -->
  <question type="formulas">
    <name>
      <text>L37- Multiplying Signed Numbers (4 in one) (parentheses)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</td>
  </tr>
  <tr><td>
    {#b}</td>
  </tr>
  <tr>
    <td>{#c}</td>
      </tr> <tr>
    <td>{#d}</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');
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        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
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        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></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>num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</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[<h3 style="text-align: left;">{A}({B}) = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">{A}({B}) = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><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>
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 <placeholder>
  <text>#b</text>
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 <answermark>
  <text>0.25</text>
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 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[1];
b=num2[1];
Sa=signA[1];
Sb=signB[1];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</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[<h3></h3><h3></h3><h3>{A}({B}) = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span><h3><span>{A}({B}) = {ans}</span></h3></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></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>0.25</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[2];
b=num2[2];
Sa=signA[2];
Sb=signB[2];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</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[<h3></h3><h3>{A}({B}) = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span><h3><span>{A}({B}) = {ans}</span></h3></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></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>0.25</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[3];
b=num2[3];
Sa=signA[3];
Sb=signB[3];
A=Sa*a;
B=Sb*b;
ans=A*B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A*B</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[<h3></h3><h3></h3><h3>{A}({B}) = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span><h3><span>{A}({B}) = {ans}</span></h3></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></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 #5/L38 - Metric System- Review of Statistics</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 358835  -->
  <question type="formulas">
    <name>
      <text>L38   CM to MM</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Convert {cm} centimeters to mm.
<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;">To convert CM to MM multiply by 10.</p><p dir="ltr" style="text-align: left;">({cm})(10) = {mm} mm&nbsp;</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>cm={1:30:1};</text>
</varsrandom>
<varsglobal><text>mm=cm*10;</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>mm</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;">{cm}cm = {_0}mm</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: 358838  -->
  <question type="formulas">
    <name>
      <text>L38   M to CM</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Convert {m} meters to cm.
<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;">To convert M to CM multiply by 100.</p><p dir="ltr" style="text-align: left;">({m})(100) = {cm} cm&nbsp;</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>m={1:30:1};</text>
</varsrandom>
<varsglobal><text>cm=m*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>cm</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;">{m}m = {_0}cm</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: 358836  -->
  <question type="formulas">
    <name>
      <text>L38   MM to CM</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Convert {mm} millimeters to cm.
<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;">To convert mm to cm divide by 10.</p><p dir="ltr" style="text-align: left;">{mm}÷10 = {cm} cm&nbsp;</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>cm={1:30:1};</text>
</varsrandom>
<varsglobal><text>mm=cm*10;</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>cm</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;">{mm}mm = {_0}cm</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: 358837  -->
  <question type="formulas">
    <name>
      <text>L38-Metric Conversions</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Convert {startV} {startU} to {endU}.</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;">To convert {startU} to {endU} {FB} {startU} by {factor}</p><p dir="ltr" style="text-align: left;">{startV} {startU} {FBsymbol} {factor} = {endV} {endU}</p><p dir="ltr" style="text-align: left;"><br></p><p dir="ltr" style="text-align: left;"><br></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>mm={1000:3000000:1000};
randUnit=shuffle([0,1,2,3]);</text>
</varsrandom>
<varsglobal><text><![CDATA[cm=mm/10;
m=cm/100;
km=m/1000;
values=[mm,cm,m,km];
units=["mm","cm","m","km"];
startV=values[randUnit[0]];
startU=units[randUnit[0]];
endV=values[randUnit[1]];
endU=units[randUnit[1]];
factor=pick(startV>endV,endV/startV,startV/endV);
FB=pick(startV>endV,"multiply","divide");
FBsymbol=pick(startV>endV,"x"," divided by ");
]]></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>endV</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;">&nbsp;{startV} {startU} = {_0} {endU}<br></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: 358839  -->
  <question type="gapselect">
    <name>
      <text>L38- Order of Metric Units</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Place the metric units in order from smallest to greatest.</p><p dir="ltr" style="text-align: left;">&nbsp;[[1]],&nbsp; [[2]], decimeter, [[3]], dekameter, hectometer, [[4]]&nbsp;</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">millimeter, centimeter, decimeter, meter, dekameter, hectometer, kilometer</p>]]></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <shuffleanswers>1</shuffleanswers>
    <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/>
    <selectoption>
      <text>millimeter</text>
      <group>1</group>
    </selectoption>
    <selectoption>
      <text>centimeter</text>
      <group>1</group>
    </selectoption>
    <selectoption>
      <text>meter</text>
      <group>1</group>
    </selectoption>
    <selectoption>
      <text>kilometer</text>
      <group>1</group>
    </selectoption>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #5/L40- Classification of Triangles</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 358848  -->
  <question type="formulas">
    <name>
      <text>L40 - classify angles  triangle-missing angle C</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Triangle ABC is not drawn to scale.<br>Given: Triangle ABC 
<br>\(\angle\)A = {a} 
<br>\(\angle\)B = {b}
<br>Find:&nbsp;\(\angle\)C&nbsp;<br>
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{axis:false,grid:false,showNavigation:false,showCopyright:false,boundingbox:[-.2,1.2,1.2,-1.2]}); var pA=board.create('point',[0,0],{size:1,name:'',fixed:true}); var tA=board.create('text',[-.01,-0.01,"A"],{anchorX:'right',anchorY:'top',fixed:true});
    var pB=board.create('point',[{Xb},{Yb}],{size:1,name:'B',anchorX:'right',anchorY:'bottom',fixed:true}); var pC=board.create('point',[{Xc},{Yc}],{size:1,name:'',anchorX:'right',anchorY:'top',fixed:true}); var tC=board.create('text',[{Xc},{Yc}-0.01,"C"],{anchorX:'right',anchorY:'top',fixed:true});
    var lineAB=board.create('line',[pA,pB],{fixed:true,straightFirst:false,straightLast:false}); var lineBC=board.create('line',[pB,pC],{fixed:true,straightFirst:false,straightLast:false}); var lineAC=board.create('line',[pA,pC],{fixed:true,straightFirst:false,straightLast:false});
    var tmA=board.create('text',[0,1.1,"Drag the Measurements to the triangle."],{anchorX:'left',fontSize:10}); var mA=board.create('text',[0,.9,"{a}"],{anchorX:'left',fontSize:20}); var mB=board.create('text',[0,.75,"{b}"],{anchorX:'left',fontSize:20});
    var mC=board.create('text',[0,.6,"x"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
  <tbody><tr>
    <td>
      \(\angle\) A +&nbsp;\(\angle\) B + \(\angle\) C = 180
    </td>
    <td>
      The sum of the angles of a triangle =&nbsp;\({180}^\circ\).
    </td>
  </tr>
  <tr>
    <td>{a} + {b} +&nbsp; \(\angle\) C = 180
    </td>
    <td>
    It is given that \(\angle\) A = {a} and \(\angle\) B = {b}
    </td>
    </tr>
 <tr>
   <td>\(\angle\) C&nbsp; +&nbsp;{aPb} = 180
   </td>
   <td>
   </td>
  </tr>
  <tr>
    <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<u> -{aPb}&nbsp; &nbsp;-{aPb}
</u>
    </td>
    <td>
    </td>
  </tr>
  <tr>
    <td>\(\angle\) C&nbsp; = {c}
  </td>
    <td>
    </td>
  </tr>
</tbody></table>]]></text>
    </generalfeedback>
    <defaultgrade>4.0000000</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>sPt={20:130:1};
s={18:70:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=sPt-s;
a=sPt;
b=90-s;
c=90-t;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
aPb=a+b;
choice=["acute","straight","obtuse","right"];
angA=(a<90)?0:((a>90)?2:3);
angC=(c<90)?0:((c>90)?2:3);
angB=(b<90)?0:((b>90)?2:3);]]></text>
</varsglobal>
<answernumbering><text>abc</text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">\(\angle\) C = {_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>
<answers>
 <partindex>
  <text>1</text>
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  <text>1</text>
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  <text>0</text>
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  <text>1</text>
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  <text></text>
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 <answer>
  <text>angA</text>
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  <text></text>
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  <text>_err == 0</text>
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  <text>1</text>
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  <text></text>
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  <text>1</text>
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  <text></text>
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 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;A:&nbsp; {_0:choice:MCE} angle.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;A = {a}</p><p dir="ltr" style="text-align: left;">&lt;A: {=choice[angA]} angle.</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
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<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>2</text>
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  <text>1</text>
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  <text>angB</text>
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  <text></text>
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  <text>_err == 0</text>
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  <text>1</text>
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  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;B:&nbsp; {_0:choice:MCE} angle</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">&lt;B = {b}</p><p dir="ltr">&lt;B: {=choice[angB]} angle.</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>
<answers>
 <partindex>
  <text>3</text>
 </partindex>
 <placeholder>
  <text></text>
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  <text>1</text>
 </answermark>
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  <text>0</text>
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  <text>1</text>
 </numbox>
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  <text></text>
 </vars1>
 <answer>
  <text>angC</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>
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 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;C:&nbsp; {_0:choice:MCE} angle</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">&lt;C = {c}</p><p dir="ltr">&lt;C: {=choice[angC]} angle.</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: 358844  -->
  <question type="formulas">
    <name>
      <text>L40 - right triangle alg expr find angs</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[\(\angle\)B is a right angle.<br>\(\angle\)C ={s}°.<br>Find the measure of&nbsp; \(\angle\)A, then classify the triangle by its angles.<br>
<p></p>
<jsxgraph width="300" height="300">
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    var pB=board.create('point',[{Xm},0],{name:'',fixed:true}); var tB=board.create('text',[{Xm},-0.07,"B"],{anchorX:'right',anchorY:'top',fixed:true}); var pC=board.create('point',[{Xm},{Ym}],{name:'C',fixed:true}); board.create('line',[pA,pB],{straightFirst:false,straightLast:false,
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    var tT=board.create('text',[{Xm},{Ym}-.1,"{s}"],{anchorX:'right'}); var tRA=board.create('text',[{Xm}-.01,0.03,"90"],{anchorX:'right'});
</jsxgraph>
<br>
<h5>Click and drag the text labels if you are unable to read them.</h5>]]></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>s={35:75:1};
X={-10:10:1};
a={2:15:1};
c={2:12:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=90-s;
ax=a*X;
cx=c*X;
b=s-ax;
d=t-cx;
aPc=a+c;
bPd=b+d;
axPb=ax+b;
cxPd=cx+d;
ninetyMbPd=90-bPd;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);
choice=["acute triangle","obtuse triangle","right triangle"];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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  <text>0</text>
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  <text>t</text>
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  <text>_err == 0</text>
 </correctness>
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  <text>1</text>
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  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<strong>\(\angle\)CAB= {_0}°<br></strong><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[The sum of the angles of a triangle =&nbsp;\({180}^\circ\).<br>It is given that \(\angle\) B = \({90}^\circ\) and &nbsp;\(\angle\) C = \({{s}}^\circ\).<br><br>The drawing states that&nbsp;\(\angle\) A = \({x}^\circ\)<br><br>
<table>
    <tbody>
        <tr>
            <td width="40%">x + {s} + 90 = \({180}^\circ\)
            </td>
            <td></td>
            <td>
                The sum of the angles = \({180}^\circ\)
            </td>
        </tr>
        <tr>
            <td>x + {=s+90}&nbsp;= \({180}^\circ\)</td>
            <td></td>
            <td>Simplify on the left side of the equation</td>
        </tr>
        <tr>
            <td>&nbsp; &nbsp;- {=s+90}&nbsp;= - {=s+90}&nbsp;<br></td>
            <td></td>
            <td>Subtract&nbsp;{=s+90} from both sides</td>
        </tr>
        <tr>
            <td>x = \({{t}}^\circ\)</td>
            <td></td>
            <td>\(\angle\) A = \({{t}}^\circ\)
            </td>
        </tr>
    </tbody>
</table><br><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>1</text>
 </partindex>
 <placeholder>
  <text></text>
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  <text>1</text>
 </answermark>
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  <text>0</text>
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  <text>1</text>
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  <text></text>
 </vars1>
 <answer>
  <text>2</text>
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  <text></text>
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  <text>_err == 0</text>
 </correctness>
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  <text>1</text>
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  <text></text>
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  <text>1</text>
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 <otherrule>
  <text></text>
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 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">The triangle is classified as a {_0:choice:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">A triangle that has a right angle is classified as a <strong>right triangle</strong>.</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358845  -->
  <question type="formulas">
    <name>
      <text>L40 - right triangle measurement</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[\(\angle\)ABC is a right angle.<br>Find the measure of \(\angle\)ACB given that \(\angle\)CAB={s}°
<br>
<p></p>
<jsxgraph width="300" height="300">
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</jsxgraph>
<br>
<h5>Click and drag the text labels if you are unable to read them.</h5>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[The sum of the angles of a triangle =&nbsp;\({180}^\circ\).<br>It is given that \(\angle\) B = \({90}^\circ\).<br>180-90 = 90.<br>The sum of the two unknown angles = \({90}^\circ\)<br>{s} + x = \({90}^\circ\)<br><u> -{s}&nbsp; &nbsp; &nbsp; &nbsp; -{s}</u><br>x= {t}]]></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>s={35:75:1};
X={-10:10:1};
a={2:15:1};
c={2:12:1};</text>
</varsrandom>
<varsglobal><text>t=90-s;
ax=a*X;
cx=c*X;
b=s-ax;
d=t-cx;
aPc=a+c;
bPd=b+d;
axPb=ax+b;
cxPd=cx+d;
ninetyMbPd=90-bPd;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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  <text>0</text>
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  <text>1</text>
 </numbox>
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  <text></text>
 </vars1>
 <answer>
  <text>t</text>
 </answer>
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  <text></text>
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  <text>_err == 0</text>
 </correctness>
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  <text>1</text>
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  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<strong>\(\angle\)ACB={_0}&nbsp;°</strong><br>]]></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: 358865  -->
  <question type="formulas">
    <name>
      <text>L40 - right triangle measurement</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[\(\angle\)ABC is a right angle.<br>Find the measure of \(\angle\)ACB given that \(\angle\)CAB={s}°
<br>
<p></p>
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-.25,1.2,1.2,-.25], showCopyright: false, showNavigation: false }); var pA= board.create('point', [0,0], {name:'',fixed:true}); var tA=board.create('text',[0,-0.07,"A"],{fixed:true}); var pB=board.create('point',[{Xm},0],{name:'',fixed:true});
    var tB=board.create('text',[{Xm},-0.07,"B"],{anchorX:'right',anchorY:'top',fixed:true}); var pC=board.create('point',[{Xm},{Ym}],{name:'C',fixed:true}); board.create('line',[pA,pB],{straightFirst:false,straightLast:false, firstArrow:false,lastArrow:false}); board.create('line',[pA,pC],{straightFirst:false,straightLast:false,
    firstArrow:false,lastArrow:false}); board.create('line',[pB,pC],{straightFirst:false,straightLast:false}); var ts=board.create('text',[.05,.03,"{s}"]); var tT=board.create('text',[{Xm}-.03,{Ym}-.1,"x"],{anchorX:'right'});&nbsp; board.create('line',[[{Xm}-0.1,0],[{Xm}-0.1,0.1]],{straightFirst:false,straightLast:false, firstArrow:false,lastArrow:false,strokeColor:'green',fixed:true});
  board.create('line',[[{Xm},0.1],[{Xm}-0.1,0.1]],{straightFirst:false,straightLast:false, firstArrow:false,lastArrow:false,strokeColor:'green',fixed:true});
</jsxgraph>
<br>
<h5>Click and drag the text labels if you are unable to read them.</h5>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[The sum of the angles of a triangle =&nbsp;\({180}^\circ\).<br>It is given that \(\angle\) B = \({90}^\circ\).<br>180-90 = 90.<br>The sum of the two unknown angles = \({90}^\circ\)<br>{s} + x = \({90}^\circ\)<br><u> -{s}&nbsp; &nbsp; &nbsp; &nbsp; -{s}</u><br>x= {t}]]></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>s={35:75:1};
X={-10:10:1};
a={2:15:1};
c={2:12:1};</text>
</varsrandom>
<varsglobal><text>t=90-s;
ax=a*X;
cx=c*X;
b=s-ax;
d=t-cx;
aPc=a+c;
bPd=b+d;
axPb=ax+b;
cxPd=cx+d;
ninetyMbPd=90-bPd;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);</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>t</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>\(\angle\)ACB={_0}&nbsp;°</strong><br>]]></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: 358846  -->
  <question type="formulas">
    <name>
      <text>L40 - rt tri alg expr find angs-QII</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[\(\angle\)B is a right angle.<br>\(\angle\)C = {t}°<br>Find the measure of \(\angle\)A&nbsp;&nbsp;<br><br>
<p></p>
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,.25,-.25], showCopyright: false, showNavigation: false }); var pA= board.create('point', [0,0], {name:'',fixed:true}); var tA=board.create('text',[0,-0.07,"A"],{fixed:true}); var pB=board.create('point',[-{Xm},0],{name:'',fixed:true});
    var tB=board.create('text',[-{Xm}-.03,-0.03,"B"],{anchorX:'right',anchorY:'bottom',fixed:true}); var pC=board.create('point',[-{Xm},{Ym}],{name:'C',fixed:true}); board.create('line',[pA,pB],{straightFirst:false,straightLast:false, firstArrow:false,lastArrow:false}); board.create('line',[pA,pC],{straightFirst:false,straightLast:false,
    firstArrow:false,lastArrow:false}); board.create('line',[pB,pC],{straightFirst:false,straightLast:false}); var ts=board.create('text',[-.03,.03,"x"],{anchorX:'right'}); var tT=board.create('text',[-{Xm}+.03,{Ym}-.1,"{t}"],{anchorX:'left'}); var tRA=board.create('text',[-{Xm}+.1,0.03,"90"],{anchorX:'right'});
</jsxgraph>
<br>
<h5>Click and drag the text labels if you are unable to read them.</h5>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[The sum of the angles of a triangle =&nbsp;\({180}^\circ\).<br>It is given that \(\angle\) B = \({90}^\circ\) and \(\angle\)C = {t}°.<br><br><table>
    <tbody>
        <tr>
            <td>x + {t} + 90 = \({180}^\circ\)
            </td>
            <td></td>
            <td>
                The sum of the angles = \({180}^\circ\)
            </td>
        </tr>
        <tr>
            <td>x + {=90+t} = 180</td>
            <td></td>
            <td>Add {t} + 90</td>
        </tr>
        <tr>
            <td>-{=90+t}&nbsp; &nbsp;&nbsp;-{=90+t}</td>
            <td></td>
            <td>Subtract&nbsp;-{=90+t} from both sides</td>
        </tr>
        <tr>
            <td>x = {s}</td>
            <td></td>
            <td>Simplify</td>
        </tr>
        <tr>
            <td>&nbsp; &nbsp; &nbsp; &nbsp;\(\angle\)A = {s}°.</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>s={35:75:1};
X={-10:10:1};
a={2:15:1};
c={2:12:1};</text>
</varsrandom>
<varsglobal><text>t=90-s;
ax=a*X;
cx=c*X;
b=s-ax;
d=t-cx;
aPc=a+c;
bPd=b+d;
axPb=ax+b;
cxPd=cx+d;
ninetyMbPd=90-bPd;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
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  <text></text>
 </placeholder>
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  <text>1</text>
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  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>s</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>\(\angle\)A= {_0} °</strong><br>]]></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: 358849  -->
  <question type="formulas">
    <name>
      <text>L40-  angle-classify  triangle-missing angle-A</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr"></p>Given: Triangle ABC 
<br>\(\angle\)B = {b} 
<br>\(\angle\)C = {c}
<br>Find:&nbsp;\(\angle\)A, then classify the triangle<br>
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{axis:false,grid:false,showNavigation:false,showCopyright:false,boundingbox:[-.2,1.2,1.2,-1.2]}); var pA=board.create('point',[0,0],{size:1,name:'',fixed:true}); var tA=board.create('text',[-.01,-0.01,"A"],{anchorX:'right',anchorY:'top',fixed:true});
    var pB=board.create('point',[{Xb},{Yb}],{size:1,name:'B',anchorX:'right',anchorY:'bottom',fixed:true}); var pC=board.create('point',[{Xc},{Yc}],{size:1,name:'',anchorX:'right',anchorY:'top',fixed:true}); var tC=board.create('text',[{Xc},{Yc}-0.01,"C"],{anchorX:'right',anchorY:'top',fixed:true});
    var lineAB=board.create('line',[pA,pB],{fixed:true,straightFirst:false,straightLast:false}); var lineBC=board.create('line',[pB,pC],{fixed:true,straightFirst:false,straightLast:false}); var lineAC=board.create('line',[pA,pC],{fixed:true,straightFirst:false,straightLast:false});
    var tmA=board.create('text',[0,1.1,"Drag the Measurements to the triangle."],{anchorX:'left',fontSize:10}); var mA=board.create('text',[0,.9,"x"],{anchorX:'left',fontSize:20}); var mB=board.create('text',[0,.75,"{b}"],{anchorX:'left',fontSize:20});
    var mC=board.create('text',[0,.6,"{c}"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
  <tbody><tr>
    <td>
      \(\angle\) A +&nbsp;\(\angle\) B + \(\angle\) C = 180
    </td>
    <td>
      The sum of the angles of a triangle =&nbsp;\({180}^\circ\).
    </td>
  </tr>
  <tr>
    <td>\(\angle\) A + {b} +&nbsp; {c} = 180
    </td>
    <td>
    It is given that \(\angle\) B = {b} and \(\angle\) C = {c}
    </td>
    </tr>
 <tr>
   <td>\(\angle\) A&nbsp; +&nbsp;{bPc} = 180
   </td>
   <td>
   </td>
  </tr>
  <tr>
    <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<u> -{bPc}&nbsp; &nbsp;-{bPc}
</u>
    </td>
    <td>
    </td>
  </tr>
  <tr>
    <td>\(\angle\) A&nbsp; = {a}
  </td>
    <td>
    </td>
  </tr>
</tbody></table>]]></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>sPt={20:130:1};
s={41:70:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=sPt-s;
a=sPt;
b=90-s;
c=90-t;

angleA=(a<90)?0:((a>90)?1:2);
angleB=(b<90)?0:((b>90)?1:2);
angleC=(c<90)?0:((c>90)?1:2);
ansChoice=angleA+angleB+angleC;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
bPc=b+c;
choice=["acute","obtuse","right"];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
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  <text>1</text>
 </answermark>
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  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>a</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;">\(\angle\) A = {_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>
<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>ansChoice</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 triangle is classified as a(n) {_0:choice:MCE} triangle</p><br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358850  -->
  <question type="formulas">
    <name>
      <text>L40-  classify Triangle</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr"></p>Given: Triangle ABC,&nbsp; \(\angle\)B = {b},&nbsp;\(\angle\)C = {c}, and&nbsp;&nbsp;\(\angle\)A = {a}<br>Classify the triangle<br>
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    var board = JXG.JSXGraph.initBoard(BOARDID,{axis:false,grid:false,showNavigation:false,showCopyright:false,boundingbox:[-.2,1.2,1.2,-1.2]}); var pA=board.create('point',[0,0],{size:1,name:'',fixed:true}); var tA=board.create('text',[-.01,-0.01,"A"],{anchorX:'right',anchorY:'top',fixed:true});
    var pB=board.create('point',[{Xb},{Yb}],{size:1,name:'B',anchorX:'right',anchorY:'bottom',fixed:true}); var pC=board.create('point',[{Xc},{Yc}],{size:1,name:'',anchorX:'right',anchorY:'top',fixed:true}); var tC=board.create('text',[{Xc},{Yc}-0.01,"C"],{anchorX:'right',anchorY:'top',fixed:true});
    var lineAB=board.create('line',[pA,pB],{fixed:true,straightFirst:false,straightLast:false}); var lineBC=board.create('line',[pB,pC],{fixed:true,straightFirst:false,straightLast:false}); var lineAC=board.create('line',[pA,pC],{fixed:true,straightFirst:false,straightLast:false});
    var tmA=board.create('text',[0,1.1,"Drag the Measurements to the triangle."],{anchorX:'left',fontSize:10}); var mA=board.create('text',[0,.9,"{a}"],{anchorX:'left',fontSize:20}); var mB=board.create('text',[0,.75,"{b}"],{anchorX:'left',fontSize:20});
    var mC=board.create('text',[0,.6,"{c}"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></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>sPt={20:130:1};
s={41:70:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=sPt-s;
a=sPt;
b=90-s;
c=90-t;

angleA=(a<90)?0:((a>90)?1:2);
angleB=(b<90)?0:((b>90)?1:2);
angleC=(c<90)?0:((c>90)?1:2);
ansChoice=angleA+angleB+angleC;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
bPc=b+c;
choice=["acute","obtuse","right"];]]></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>ansChoice</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 triangle is classified as a(n) {_0:choice:MCE} triangle</p><br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[A triangle with three acute angles is an acute triangle.<br>A triangle with one obtuse angle is an obtuse triangle.<br>A triangle with one right angle is a right triangle.<br><br>Triangle ABC:&nbsp; {=choice[ansChoice]} triangle]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358853  -->
  <question type="formulas">
    <name>
      <text>L40- Equilateral</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,1.2,-1.2], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [0,0], {name:'',fixed:true});
    var tC=board.create('text',[0,-0.07,"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[theta={20:340:1};
fillC={"red","orange","green","black","blue","aqua","pink","maroon","purple"};
factor={5:50:1};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[#determine if isosceles or equilateral
difference=60;
s=theta;
Ya=sin(s*(pi()) /180);
Xa=cos(s*(pi()) /180);

t=theta-difference;
t=(t<0)?360+t:t;
Yb=sin(t*(pi()) /180);
Xb=cos(t*(pi()) /180);

disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=factor;
disBC=factor;

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=1;
ans=(theta==60)?2:ans;
ans=(difference==60)?2:ans;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
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  <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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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: 358852  -->
  <question type="formulas">
    <name>
      <text>L40- Isosceles Triangle (maybe equi)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,1.2,-1.2], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [0,0], {name:'',fixed:true});
    var tC=board.create('text',[0,-0.07,"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[theta={20:340:1};
difference={40:140:1};
factor={5:50:1};
fillC={"red","blue","green","orange","black","pink","maroon","yellow","aqua","purple"};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[#determine if isosceles or equilateral

s=theta;
Ya=sin(s*(pi()) /180);
Xa=cos(s*(pi()) /180);

t=theta-difference;
t=(t<0)?360+t:t;
Yb=sin(t*(pi()) /180);
Xb=cos(t*(pi()) /180);

disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=factor;
disBC=factor;

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=1;
ans=(theta==60)?2:ans;
ans=(difference==60)?2:ans;]]></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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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: 358854  -->
  <question type="formulas">
    <name>
      <text>L40- scalene (maybe isosc-equi)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle using the lengths of the sides.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-10,10,10,-10], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [{Xc},{Yc}], {name:'',fixed:true});
    var tC=board.create('text',[{Xc},{Yc},"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[Xa={-10:10};
Ya={-10:10};
Xb={-10:10};
Yb={-10:10};
Xc={-10:10};
Yc={-10:10};
factor={.1:2:.1};
fillC={"red","blue","green","orange","black","pink","maroon","yellow","aqua","purple"};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[slopeCB=(Yc-Yb)/(Xc=Xb);
slopeAC=(Ya-Yc)/(Xa=Xc);
Xc=(abs(slopeCB-slopeAC)<.1)?Xc+1:Xc;







disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=round(factor*pow((pow(Xa-Xc,2)+pow(Ya-Yc,2)),2),0);
disBC=round(factor*pow((pow(Xc-Xb,2)+pow(Yc-Yb,2)),2),0);

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=0;
ans=(disAC==disAB)?ans+1:ans;
ans=(disAC==disBC)?ans+1:ans;
ans=(disBC==disAB)?ans+1:ans;
]]></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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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: 358851  -->
  <question type="formulas">
    <name>
      <text>L40-Isosceles-Q1</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Given Triangle ABC, AB = {ABround}, AC={AC}, and BC={BC}</p>
<p dir="ltr" style="text-align: left;">Classify the triangle by its sides.</p>

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    var board=JXG.JSXGraph.initBoard(BOARDID,{axis:false,grid:false,boundingbox:[-.9,.9,.2,-.2], showCopyright:false, showNavigation:false}); var pA=board.create('point',[{Xa},{Ya}],{name:'A',fixed:true}); var pB=board.create('point',[0,0],{name:'B',fixed:true});
    var pC=board.create('point',[{Xc},{Yc}],{name:'',fixed:true}); var tC=board.create('text',[{Xc}+.01,{Yc}-.01,"C"],{anchorX:'left',anchorY:'top'}); var lineAB =board.create('line',[pA,pB],{straightFirst:false,straightLast:false}); var lineBC =board.create('line',[pB,pC],{straightFirst:false,straightLast:false});
    var lineAC =board.create('line',[pA,pC],{straightFirst:false,straightLast:false});&nbsp; var tAC=board.create('text',[{Xa}-.07,{Ya}/2,"{AC}"],{anchorX:'right',fontSize:20}); var tBC=board.create('text',[{Xc}/2,-.06,"{BC}"],{anchorX:'left',fontSize:20});
    var tAB=board.create('text',[{Xa}/2,{Ya}/2+.11,"{ABround}"],{anchorX:'left',anchorY:'top',fontSize:20}); var tangB=board.create('text',[-.05,.03,"45"],{anchorX:'right',color:'#0000ff'});
</jsxgraph>]]></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>X={1:10:1};
rand=shuffle([0,1,2]);</text>
</varsrandom>
<varsglobal><text><![CDATA[AC=X;
BC=X;
AB=X*sqrt(2);
ABround=round(AB,2);
Xa=-sqrt(2)/2;
Ya=sqrt(2)/2;
Xc=-sqrt(2)/2;
Yc=0;
AC2=AC*AC;
BC2=BC*BC;
AC2PBC2=AC2+BC2;
choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>0</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>rand[_0]=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;">Triangle ABC:&nbsp; {_0:choice:MCE} triangle</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[Two sides of triangle ABC are equal in measure.<br><br>scalene triangle:&nbsp; none of the sides are equal in measure<br>isosceles triangle:&nbsp; two sides are equal in measure<br>equilateral triangle: all three sides are equal in measure<br><br>The triangle is an isosceles triangle<br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358855  -->
  <question type="formulas">
    <name>
      <text>L40-scalene Triangle (maybe equi) angles</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,1.2,-1.2], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [{Xc},{Yc}], {name:'',fixed:true});
    var tC=board.create('text',[{Xc},{Yc},"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[theta={60:120:1};
difference={60:120:1};
third={60:120:1};
factor={5:50:1};
fillC={"red","blue","green","orange","black","pink","maroon","yellow","aqua","purple"};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[#determine if isosceles or equilateral

s=theta;
Ya=sin(s*(pi()) /180);
Xa=cos(s*(pi()) /180);

t=theta-difference;
t=(t<0)?360+t:t;
Yb=sin(t*(pi()) /180);
Xb=cos(t*(pi()) /180);

x=theta-difference-third;
x=(t<0)?360+x:x;
Yc=sin(x*(pi()) /180);
Xc=cos(x*(pi()) /180);

disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=round(factor*pow((pow(Xa-Xc,2)+pow(Ya-Yc,2)),2),0);
disBC=round(factor*pow((pow(Xc-Xb,2)+pow(Yc-Yb,2)),2),0);

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=0;
ans=(disAC==disAB)?ans+1:ans;
ans=(disAC==disBC)?ans+1:ans;
ans=(disBC==disAB)?ans+1:ans;
]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
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  <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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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: 358847  -->
  <question type="formulas">
    <name>
      <text>L40-triangle-missing angle B</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC 
<br>\(\angle\)A = {a} 
<br>\(\angle\)C = {c}
<br>Find:&nbsp;\(\angle\)B&nbsp;<br>
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{axis:false,grid:false,showNavigation:false,showCopyright:false,boundingbox:[-.2,1.2,1.2,-1.2]}); var pA=board.create('point',[0,0],{size:1,name:'',fixed:true}); var tA=board.create('text',[-.01,-0.01,"A"],{anchorX:'right',anchorY:'top',fixed:true});
    var pB=board.create('point',[{Xb},{Yb}],{size:1,name:'B',anchorX:'right',anchorY:'bottom',fixed:true}); var pC=board.create('point',[{Xc},{Yc}],{size:1,name:'',anchorX:'right',anchorY:'top',fixed:true}); var tC=board.create('text',[{Xc},{Yc}-0.01,"C"],{anchorX:'right',anchorY:'top',fixed:true});
    var lineAB=board.create('line',[pA,pB],{fixed:true,straightFirst:false,straightLast:false}); var lineBC=board.create('line',[pB,pC],{fixed:true,straightFirst:false,straightLast:false}); var lineAC=board.create('line',[pA,pC],{fixed:true,straightFirst:false,straightLast:false});
    var tmA=board.create('text',[0,1.1,"Drag the Measurements to the triangle."],{anchorX:'left',fontSize:10}); var mA=board.create('text',[0,.9,"{a}"],{anchorX:'left',fontSize:20}); var mB=board.create('text',[0,.75,"x"],{anchorX:'left',fontSize:20});
    var mC=board.create('text',[0,.6,"{c}"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
  <tbody><tr>
    <td>
      \(\angle\) A +&nbsp;\(\angle\) B + \(\angle\) C = 180
    </td>
    <td>
      The sum of the angles of a triangle =&nbsp;\({180}^\circ\).
    </td>
  </tr>
  <tr>
    <td>{a} + \(\angle\) B + {c} = 180
    </td>
    <td>
    It is given that \(\angle\) A = {a} and \(\angle\) C = {c}
    </td>
    </tr>
 <tr>
   <td>\(\angle\) B&nbsp; +&nbsp;{aPc} = 180
   </td>
   <td>
   </td>
  </tr>
  <tr>
    <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<u> -{aPc}&nbsp; &nbsp;-{aPc}
</u>
    </td>
    <td>
    </td>
  </tr>
  <tr>
    <td>\(\angle\) B&nbsp; = {b}
  </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>sPt={20:130:1};
s={18:70:1};</text>
</varsrandom>
<varsglobal><text>t=sPt-s;
a=sPt;
b=90-s;
c=90-t;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
aPc=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>b</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;">\(\angle\) B = {_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: 358856  -->
  <question type="formulas">
    <name>
      <text>L40-Warmup01- angle classification- compass- enter measurement (Pull down answer) (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3><strong><span style="color: rgb(51, 102, 255);"><strong style="color: rgb(73, 80, 87);">Classify \(\angle\)ABC, then m</strong></span></strong><strong style="font-size: 1.64062rem;"><span><strong>easure \(\angle\)ABC</strong></span></strong></h3>

<jsxgraph width="400" height="{height}">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,1.2,-.2], showCopyright: false, showNavigation: false,keepaspectratio:true });
    var im = board.create('image', ['http://hshonorroll.com/graphics4Class/compass-square.png',
    [-0.9,-.0625], [4,4]],{fixed:true});
    im.setSize(1.8,1.8);
    board.update();
    var pA= board.create('point', [0,0], {name:'',size:0,fixed:true,showInfobox:false});

    var tA=board.create('text',[0,-.1,"B"],{fixed:true});
    var pBL= board.create('point', [0,1], {name:' ',size:0,fixed:true,showInfobox:false});
    var tBL = board.create('text',[{Xm},{Ym}+.1,"A"],{fixed:true});
    var pC=board.create('point',[1,0],{name:' ',fixed:true,size:0,showInfobox:false});
    var tC=board.create('text',[1,-.1,"C"],{fixed:true});
    var pCR=board.create('point',[1.0,0],{name:' ',size:0,fixed:true,showInfobox:false});
    var pD=board.create('point',[{Xm},{Ym}],{name:'',fixed:true,size:0,showInfobox:false}); board.create('line',[pA,pCR],{straightFirst:false,straightLast:false,
    firstArrow:false,lastArrow:true});

    var pt=board.create('point',[{Xt},{Yt}],{name:'D',fixed:true,size:0,showInfobox:false});
    board.create('line',[pA,pt],{straightFirst:false,straightLast:false, firstArrow:false,lastArrow:true});

    board.create('line',[pA,[-1,0]],{straightFirst:false,straightLast:false,lastArrow:true});

    board.create('line',[pA,pD],{straightFirst:false,straightLast:false,lastArrow:true});
    var tC=board.create('text',[-1,-.1,"F"],{fixed:true});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<strong>\(\angle\)ABC&nbsp;is classified as a(n) {=angle[ans]}.</strong><br><img src="@@PLUGINFILE@@/angles_classify.png" alt="classify angles" width="400" height="150" role="presentation" class="img-fluid atto_image_button_text-bottom">]]></text>
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    </generalfeedback>
    <defaultgrade>3.0000000</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>s={20:170:1};
randOrder=shuffle([0,1,2,3]);
randOrder1=shuffle([0,1,2,3]);
randOrder2=shuffle([0,1,2,3]);</text>
</varsrandom>
<varsglobal><text><![CDATA[s=57;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);

t=120;
Yt=sin(t*(pi()) /180);
Xt=cos(t*(pi()) /180);
tMs=t-s;
height= ((180-s > 150) || ( 30-s>0))?100:250;

angle=["acute angle","right angle","obtuse angle","straight angle"];
ans=(s<90)?0:-1;
ans=(s==90)?1:ans;
ans=(s>90 && s<180)?2:ans;
ans=(s==180)?3:ans;
deg=[s,180-s,pick(s>90,175-s,170+s),pick(s>90,s+10,s-2*(s%10))];
degAns=[deg[randOrder[0]],deg[randOrder[1]],deg[randOrder[2]],deg[randOrder[3]]];
measure=(randOrder[0]==0)?0:-1;
measure=(randOrder[1]==0)?1:measure;
measure=(randOrder[2]==0)?2:measure;
measure=(randOrder[3]==0)?3:measure;

#Calculate angle t
anst=(tMs<90)?0:-1;
anst=(tMs==90)?1:ans;
anst=(tMs>90 && tMs<180)?2:ans;
anst=(tMs==180)?3:ans;
degt=[tMs,180-tMs,pick(tMs>90,175-tMs,170+tMs),pick(tMs>90,tMs+10,tMs-2*(tMs%10))];
degAnst=[degt[randOrder1[0]],degt[randOrder1[1]],degt[randOrder1[2]],degt[randOrder1[3]]];
measuret=(randOrder1[0]==0)?0:-1;
measuret=(randOrder1[1]==0)?1:measuret;
measuret=(randOrder1[2]==0)?2:measuret;
measuret=(randOrder1[3]==0)?3:measuret;

F=180-t;
ansF=(F<90)?0:-1;
ansF=(F==90)?1:ans;
ansF=(F>90 && F<180)?2:ans;
ansF=(F==180)?3:ans;
degF=[F,180-F,pick(F>90,175-F,170+F),pick(F>90,F+10,F-2*(F%10))];
degAnsF=[degF[randOrder2[0]],degF[randOrder2[1]],degF[randOrder2[2]],degF[randOrder2[3]]];
measureF=(randOrder2[0]==0)?0:-1;
measureF=(randOrder2[1]==0)?1:measureF;
measureF=(randOrder2[2]==0)?2:measureF;
measureF=(randOrder2[3]==0)?3:measureF;

]]></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>[ans,measure]</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 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>
<p>&lt; ABC is a(n) {_0:angle:MCE}, it measures {_1:degAns:MCE} degrees.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">acute &lt;ABC measures {s}º</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>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[anst,measuret]</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> &lt; ABD is a(n) {_0:angle:MCE}, it measures {_1:degAnst:MCE} degrees.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">acute &lt;ABD measures {tMs}º<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>2</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>[ansF,measureF]</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;">&lt; DBF is a(n) {_0:angle:MCE}, it measures {_1:degAnsF:MCE} degrees.<br><br></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">acute &lt;DBF measures {F}º<br></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 358857  -->
  <question type="formulas">
    <name>
      <text>TL40-Warmup02-angle classification- acute, right, obtuse, straight (copy)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p><strong style="font-size: 0.9375rem;">\(\angle\)ABC measures {s}°.&nbsp;&nbsp;Classify \(\angle\)ABC.</strong><br></p>
<jsxgraph width="400" height="{height}">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1,1.1,1.1,-.1], showCopyright: false, showNavigation: false,keepaspectratio:true }); var pA= board.create('point', [0,0], {name:'',fixed:true}); var tA=board.create('text',[0,-.05,"B"],{fixed:true}); var pBL= board.create('point', [0,1.99], {name:' ',size:0,fixed:true}); var pC=board.create('point',[1,0],{name:' ',fixed:true}); var tC=board.create('text',[1,-.05,"C"],{fixed:true});
    var pCR=board.create('point',[1.0,0],{name:' ',size:0,fixed:true}); var pD=board.create('point',[{Xm},{Ym}],{name:'A',fixed:true}); board.create('line',[pA,pCR],{straightFirst:false,straightLast:false,
    firstArrow:false,lastArrow:true}); board.create('line',[pA,pD],{straightFirst:false,straightLast:true,lastArrow:true}); var ts=board.create('text',[.125,.125,"{s}"]); </jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<strong>\(\angle\)ABC measures {s}°.&nbsp; <br>\(\angle\)ABC&nbsp;is classified as a(n) {=angle[ans]}.</strong><br><img src="@@PLUGINFILE@@/angles_classify.png" alt="classify angles" width="400" height="150" role="presentation" class="img-fluid atto_image_button_text-bottom">]]></text>
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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>s={20:180:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);
height= ((180-s > 150) || ( 30-s>0))?100:250;
angle=["acute angle","right angle","obtuse angle","straight angle"];
ans=(s<90)?0:-1;
ans=(s==90)?1:ans;
ans=(s>90 && s<180)?2:ans;
ans=(s==180)?3:ans;]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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  <text>1</text>
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 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
 </correctness>
 <unitpenalty>
  <text>1</text>
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 <postunit>
  <text></text>
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 <ruleid>
  <text>1</text>
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 <subqtext format="html">
<text><![CDATA[&lt; ABC is a {_0:angle: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: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #5/L33 -Scientific Notation</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 359206  -->
  <question type="formulas">
    <name>
      <text>L33- expanded to SciNotation</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What is {expanded} written in scientific notation?&nbsp;</p><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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    document.write('<canvas id="canvas_1" style="display: none;"></canvas>');

    function newWidth() {
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        $(".formulas_number").css("padding-left", "10px");
        newWidth();
        $(".formulas_number").keyup(function() {
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
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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>randOrderN = shuffle([0:4]);
randOrderE = shuffle([0:4]);
number={1.001:9.998:.001};
exponent={3:6:1};</text>
</varsrandom>
<varsglobal><text>expanded=number*pow(10,exponent);
Nums=[number,number*10,number*100,number*1000];
Exps=[exponent,exponent-1,exponent-2,exponent-3];
ansNums=[Nums[randOrderN[0]],Nums[randOrderN[1]],Nums[randOrderN[2]],Nums[randOrderN[3]]];
ansExps=[Exps[randOrderE[0]],Exps[randOrderE[1]],Exps[randOrderE[2]],Exps[randOrderE[3]]];</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>[number,exponent]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[(_0 == number) &&(_1 == exponent)]]></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[<h3 style="text-align: left;">{_0} x 10<sup> {_1}</sup></h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(255, 51, 102);">{number}</span> x <span class="" style="color: rgb(51, 102, 255);">10</span><sup><span class="" style="color: rgb(51, 102, 255);">{exponent}</span> </sup>= {expanded}</p><p dir="ltr" style="text-align: left;">The factor must be between 1 and 10:&nbsp; <strong><span class="" style="color: rgb(255, 51, 102);">{number}</span></strong></p><p dir="ltr" style="text-align: left;"><span><span class="" style="color: rgb(51, 51, 51);">The power of 10:&nbsp;<strong><span class="" style="color: rgb(51, 102, 255);">10<sup>{exponent}</sup> </span></strong>because the decimal moves <span class="" style="color: rgb(51, 102, 255);">{exponent}</span> places.</span></span></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359204  -->
  <question type="formulas">
    <name>
      <text>L33- Multiple choice expanded to SciNotation</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">What is {expanded} written in scientific notation?&nbsp;</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>randOrderN = shuffle([0:4]);
randOrderE = shuffle([0:4]);
number={1.001:9.998:.001};
exponent={3:6:1};</text>
</varsrandom>
<varsglobal><text>expanded=number*pow(10,exponent);
Nums=[number,number*10,number*100,number*1000];
Exps=[exponent,exponent-1,exponent-2,exponent-3];
ansNums=[Nums[randOrderN[0]],Nums[randOrderN[1]],Nums[randOrderN[2]],Nums[randOrderN[3]]];
ansExps=[Exps[randOrderE[0]],Exps[randOrderE[1]],Exps[randOrderE[2]],Exps[randOrderE[3]]];</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>[1,1]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[(randOrderN[_0] == 0) &&(randOrderE[_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[<h3 style="text-align: left;">{_0:ansNums:MCE} x 10<sup> {_1:ansExps:MCE}</sup></h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"><span class="" style="color: rgb(255, 51, 102);">{number}</span> x <span class="" style="color: rgb(51, 102, 255);">10</span><sup><span class="" style="color: rgb(51, 102, 255);">{exponent}</span> </sup>= {expanded}</p><p dir="ltr" style="text-align: left;">The factor must be between 1 and 10:&nbsp; <strong><span class="" style="color: rgb(255, 51, 102);">{number}</span></strong></p><p dir="ltr" style="text-align: left;"><span><span class="" style="color: rgb(51, 51, 51);">The power of 10:&nbsp;<strong><span class="" style="color: rgb(51, 102, 255);">10<sup>{exponent}</sup> </span></strong>because the decimal moves <span class="" style="color: rgb(51, 102, 255);">{exponent}</span> places.</span></span></p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359205  -->
  <question type="formulas">
    <name>
      <text>L33- Scientific Notation - to expanded notation</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Write {number} x 10<sup>{exponent}</sup>&nbsp;in expanded notation.&nbsp; (Do not use commas)</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></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={1.12:9.98:.001};
exponent={2:6:1};</text>
</varsrandom>
<varsglobal><text>expanded=number*pow(10,exponent);</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>[expanded]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.001]]></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[<h3 style="text-align: left;">{_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p>
<h3><span class="" style="color: rgb(255, 51, 102);">{number}</span> x <span class="" style="color: rgb(51, 102, 255);">10</span><sup><span class="" style="color: rgb(51, 102, 255);">{exponent}</span></sup><span class="" style="color: rgb(51, 51, 51);">= {expanded}</span></h3>

<p><span class="" style="color: rgb(255, 51, 102);">The factor is between 1 and 10.</span></p><p><span class="" style="color: rgb(51, 102, 255);">Move the decimal {exponent} places to the right since 10<sup>{exponent}</sup> is {=pow(10,exponent)}.</span></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 #5/L39- Division Integers</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 359828  -->
  <question type="formulas">
    <name>
      <text>L39- Divide Signed Numbers (4 in one)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</td>
  </tr>
  <tr><td>
    {#b}</td>
  </tr>
  <tr>
    <td>{#c}</td>
      </tr> <tr>
    <td>{#d}</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>
    </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>num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3 style="text-align: left;">{A} ÷ {B} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">{A} ÷ {B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><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>#b</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[1]*num2[1];
b=num2[1];
Sa=signA[1];
Sb=signB[1];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3></h3><h3>{A}&nbsp;÷&nbsp;{B} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span>{A} ÷ {B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></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>0.25</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[2]*num2[2];
b=num2[2];
Sa=signA[2];
Sb=signB[2];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3>{A}÷{B} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span>{A} ÷ {B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></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>0.25</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[3]*num2[3];
b=num2[3];
Sa=signA[3];
Sb=signB[3];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3></h3><h3>{A}&nbsp;÷&nbsp;{B} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span>{A}÷{B} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359830  -->
  <question type="formulas">
    <name>
      <text>L39- Divide Signed Numbers (fraction bar)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</td>
  </tr>
  <tr><td>
    {#b}</td>
  </tr>
  <tr>
    <td>{#c}</td>
      </tr> <tr>
    <td>{#d}</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>
    </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>num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3 style="text-align: left;">\(  \frac{{A}}{{B}}  \)&nbsp;= {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;"><h3>\( \frac{{A}}{{B}} \) = {ans}</h3></span></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><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>#b</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[1]*num2[1];
b=num2[1];
Sa=signA[1];
Sb=signB[1];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3></h3><h3></h3><h3>\( \frac{{A}}{{B}} \) = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span><h3>\( \frac{{A}}{{B}} \) = {ans}</h3></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></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>
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  <text>0.25</text>
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  <text>0</text>
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  <text><![CDATA[a=num1[2]*num2[2];
b=num2[2];
Sa=signA[2];
Sb=signB[2];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3></h3><h3>\( \frac{{A}}{{B}} \) = {_0}</h3>]]></text>
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 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span><span><span><strong><h3>\( \frac{{A}}{{B}} \) = {ans}</h3></strong></span></span></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></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>0.25</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[3]*num2[3];
b=num2[3];
Sa=signA[3];
Sb=signB[3];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",abs(a/b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>A/B</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[<h3></h3><h3></h3><h3>\( \frac{{A}}{{B}} \) = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<h3></h3><h3><span><h3>\( \frac{{A}}{{B}} \) = {ans}</h3></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><h3></h3>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359829  -->
  <question type="formulas">
    <name>
      <text>L39- Dividing Integers (div sign)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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 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></text>
    </generalfeedback>
    <defaultgrade>0.2500000</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>num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",a/b);
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
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 <unitpenalty>
  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<h3><span>{A} ÷ {B}= {_0}</span></h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p>
<h3><span style="font-size: 1.64062rem;">
        <h3><span>{A} ÷ {B} = {ans}
    </span></h3>
<p></p>
<h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3>
<div class="editor-indent" style="margin-left: 30px;">
    <h3>{Action}</h3>
</div>
<h3>{Work}</h3>
<h3>{SignAns}</h3><br>
<p></p></span></h3>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359827  -->
  <question type="formulas">
    <name>
      <text>L39- Dividing Integers (fraction bar)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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'
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    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></text>
    </generalfeedback>
    <defaultgrade>0.2500000</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>num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",a/b);
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
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  <text>1</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<h3><span>\(\frac{{A}}{{B}}\)= {_0}</span></h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">\(\frac{{A}}{{B}}\) = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><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 #5/L38 - Metric System- Review of Statistics/L38- Conversion Tables</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 359909  -->
  <question type="formulas">
    <name>
      <text>L38-km-mm Metric Conversions (table)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Fill in the table with the metric conversions.<br>
<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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    var defaultWidth = 110;
    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));
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        var ctx = c.getContext("2d");
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        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;"></p>
<img src="@@PLUGINFILE@@/image%20%281%29.png" alt="" role="presentation" class="img-fluid"><br><table style="text-align: center;">
    <tbody>
        <tr>
            <td width="25%"><h5><strong>mm</strong></h5></td>
            <td width="25%"><h5><strong>cm</strong></h5></td>
            <td width="25%"><h5><strong>m</strong></h5></td>
            <td width="25%"><h5><strong>km</strong></h5></td>
        </tr>
        <tr>
            <td><p style="text-align: center;"><span style="font-size: 0.9375rem;">{cm}x10</span></p><strong><p style="text-align: center;"><strong style="font-size: 0.9375rem;">{mm}</strong></p></strong></td>
            <td><p style="text-align: center;"><span style="font-size: 0.9375rem;">{m}x100</span></p><strong><p style="text-align: center;"><strong style="font-size: 0.9375rem;">{cm}</strong></p></strong></td>
            <td><p style="text-align: center;"><span style="font-size: 0.9375rem;">{km}x1000</span></p><strong><p style="text-align: center;"><strong style="font-size: 0.9375rem;">{m}</strong></p></strong></td>
            <td>{km}</td>
        </tr>
    </tbody>
</table><br>
<p></p>]]></text>
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84CryosjKi5uYCb6RPzZs/n6i6WuxvLJxPPknU3T1WirydC7eQPfoo0Xe+Q9TamjcgBV3Q975H9N3vSuf0cpPvvJOovFx4jcXqnntCM/wOt5DBkJSyxOyll8ZCKufcCGCY9IMfWDwhZiEZErhVO5DzGH4vX070ox8lecnIIPVWYK4V/TMkS7iFjA0JYoY/jMllGR8BeLff/77FkR8O4uk6swQrDJluvTXJC+IvvJK8MO2za1dyP+CtcAvZtGlJQ2IxwySsLNkRwNslzPmgMzJHETNnhnhTCVZYMK0hvNI5gRGG3iFawi1kpgdhGhQMTV6NezcjiH97e2qnNHnKsD3JEkNKDCMh/iYj3pY5W6KQeWO4eeEWMjYecw0RExc/2fHctiBSGJJjqGRy5G0M30XILIoQMPb4MU/GjMw1RgnPP+9GvXDPQ+BDNDfGoMMrZJhMZAOCZxaLyTdQfNe8rtEx8WYJC8Tf5Amm8p1UkiTsDaKOjoqlri6VF+bLQvKpQbLSAWzBkQjhi4/wChk6mel9wcBgaPJlujfrhbGZQ3BMzMLb4A9i4VUUs2dhUuR5MbODQshMXvhmqthHAmAQUpsJr5CZhsbbeCLCwxBPgok4r9HhTBFzTmV9YiDDSmuo5OVzFAhbsYoZBAzzhyFdoiVkgAgRg5iJm+9sUuho2XyoiE8NilnM0P5sxAnzQ6bn5nwXCuso+IRwXsyEHD0hQ+0xvMTr32IzKPPOOW1jUt+LJ2a/FkZabGKG4SQ8rGzb7TQMtfMspH1MSfA8a4jbFU0hA1AYFDogxu3YLuYF3imEPdtOaTKDZ4KOXQwsmRfPF5ocvGyDETr3RHh7KSfoNOhbsIsILNEVMobLQykvcxx8TSGt4YWhU/Hbtom0DSzxQqWQPV1M4oOXHy+N8D0VxN+PvCZy3/y+Fu0BoxB9ue/WxOgLGVqIJySeHvDQCs2oMt1BzBVO1AtzypuNuNB+DgYbgej4PWENr66QpjnwEEN7IjYHXRhCxh0S8PEkwZOyUIdIEDAeBvrhhTE7+xrDJrAsBO+MvbBcee0Qf8xNRtnu0Aa2qwg6A4UlZNwZMUSCYcFLy2Vn5/LysYaAwaOA14ntfCxgB+MGyygKGuwgF15rJvYQSpQHQYvKggc+vySK4j1OcC5MIWMjgoeGjg8BiOpNQr3RBghKUKIcNUEDsyA9c37TF/aXAeypQvAjvhS2kPHNQUfE3Ag8Czx9wj7+R0eEcOHpjvqGxdVnQYNIoJOGpV64z6gbPCG8rMC9DkPdwAj3EPXJlxfNNp9pjXpgpAJOYRfaTG1wOF4cQmY23BQJiAX2w7BwvWBgqFeYxRbDEX6a4+GA7aDmJFE26oC/sHoWeCGAUQFEDV/I51tkcW8gWngAwbsf72cnYegnGepQfEJmgoB44GnJ4gEjy9WEsFkutlEOPAgYFpcfFlG113WsfXRKcEMnRVuwncuOgrzBDcIFbkEIw1g8xjrHDwCwQv3Rjlyxgi0xJ5QHIQvqYTMWE5/OFbeQmRDhcuOJDmHDkwt/MDbsQ3TGY3AwHFxrihaMCn/IF+VhSFQoC9qC+SF+OIAhvEt4TWCQTUdCXrgG+WEoBGYQLuaWb6/G73uE+rO9oV1oH9qJ9mZra2xjzN3MK+qcPHIXIRsLFAsRnmwwEp5bYMNDJ8U2/8EjYU8Bx3AN/8HYisSoUpBiiAwhs/MDJ5MVD3uYLXODJxHmYXZKYye4Ay8KHibajqEo25Xdzsx9bCM95lKzFcAJVjdMl4uQheluSF2EgBAYFwERsnFhk4uEgBAIEwERMt/uRh9RRQVRRW16jn0tRGWJ/wSFKK1lFUR96cmK78gEmRUs1xxzKUBuImRO6tFSQVTmIEhOaflYS60lUGlC1pIImZwQr75aax9iVkhL3plFlKsXThOyJTcubuejaZQiZE73zYuxOV1XW0uEP3OphSiWpXpgLGa1BeSW5ZtZVLl65TReW3Lj4nbetN0IbYuQ+XmzHI3PQdwwrtRpW/wsPZp5jZeZ03WFxNWpfU7H7G12S+N2PppWFPJ/B5c3qOxuG/NY/B+HeO3Fe0ozkjEEKy1t3hrrU0FBMosS13FySrMPL212S1OR+QGaVp5PZpKnbMQj8xO0kzE4HbM/Rf2sQ9TycuLjdMzOzEuaqLEw6+vUPqdj2XLxkodZj4hsi5A53Siv8xj2a52MpEDnJOxNp3wziypXr5zGa0tuXNzOp93YaBwQIXO6T16NzX6tk/ERDy0Sby3xRoo/wbBfH+X9vDOLKFevnMZtS25c3M5H0whFyPy6b7Vlyf9Mbf90owC/2/EF20SZFSrXXHMpQG4iZL70SMlECAiBIAmIkAVJX8oWAkLAFwIiZL5glEyEgBAIkoAIWZD0pWwhIAR8ISBC5gtGyUQICIEgCYiQBUlfyhYCQsAXAiJkvmCUTISAEAiSgAhZkPSlbCEgBHwhIELmC0bJRAgIgSAJiJAFSV/KFgJCwBcCImS+YJRMhIAQCJKACFmQ9KVsISAEfCEgQuYLRslECAiBIAn8P2SniNVICAlBAAAAAElFTkSuQmCC</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>mm={10000:3000000:10000};
randUnit=shuffle([0,1,2,3]);</text>
</varsrandom>
<varsglobal><text><![CDATA[cm=mm/10;
m=cm/100;
km=m/1000;
values=[mm,cm,m,km];
units=["mm","cm","m","km"];
startV=values[randUnit[0]];
startU=units[randUnit[0]];
endV=values[randUnit[1]];
endU=units[randUnit[1]];
factor=pick(startV>endV,endV/startV,startV/endV);
FB=pick(startV>endV,"multiply","divide");
FBsymbol=pick(startV>endV,"x"," divided by ");
]]></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>[mm,cm,m]</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;"></p>
<table>
    <tbody>
        <tr>
            <td width="25%">mm</td>
            <td width="25%">cm</td>
            <td width="25%">m</td>
            <td width="25%">km</td>
        </tr>
        <tr>
            <td>{_0}</td>
            <td>{_1}</td>
            <td>{_2}</td>
            <td>{km}</td>
        </tr>
    </tbody>
</table><br>
<p></p>]]></text>
 </subqtext>
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  </question>

<!-- question: 359910  -->
  <question type="formulas">
    <name>
      <text>L38-mm-km Metric Conversions (table)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Fill in the table with the metric conversions.<br>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
<script>
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    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"></p>
<img src="@@PLUGINFILE@@/image%20%282%29.png" alt="" role="presentation" class="img-fluid"><br>
<table width="60%">
    <tbody>
        <tr>
            <td width="25%">
                <h5 style="text-align: center;"><strong>mm</strong></h5>
            </td>
            <td width="25%">
                <h5 style="text-align: center;"><strong>cm</strong></h5>
            </td>
            <td width="25%">
                <h5 style="text-align: center;"><strong>m</strong></h5>
            </td>
            <td width="25%">
                <h5 style="text-align: center;"><strong>km</strong></h5>
            </td>
        </tr>
        <tr>
            <td>
                <strong>
                    <p style="text-align: center;"><strong style="font-size: 0.9375rem;">{mm}</strong></p>
                </strong>
            </td>
            <td>
                <strong>
                    <p style="text-align: center;"><span style="font-size: 0.9375rem;">{mm} ÷10</span></p>
                    <p style="text-align: center;"><strong style="font-size: 0.9375rem;">{cm}</strong></p>
                </strong>
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            <td>
                <strong>
                    <p style="text-align: center;"><span style="font-size: 0.9375rem;">{cm} ÷100</span></p>
                    <p style="text-align: center;"><strong style="font-size: 0.9375rem;">{m}</strong></p>
                </strong>
            </td>
            <td>
                <p style="text-align: center;"><span style="font-size: 0.9375rem;"><strong>{m} ÷1000</strong></span></p><strong><p style="text-align: center;"><strong style="font-size: 0.9375rem;">{km}</strong></p></strong></td>
        </tr>
    </tbody>
</table><br>
<p></p>]]></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>mm={1000:300000:1000};
randUnit=shuffle([0,1,2,3]);</text>
</varsrandom>
<varsglobal><text><![CDATA[cm=mm/10;
m=cm/100;
km=m/1000;
values=[mm,cm,m,km];
units=["mm","cm","m","km"];
startV=values[randUnit[0]];
startU=units[randUnit[0]];
endV=values[randUnit[1]];
endU=units[randUnit[1]];
factor=pick(startV>endV,endV/startV,startV/endV);
FB=pick(startV>endV,"multiply","divide");
FBsymbol=pick(startV>endV,"x"," divided by ");
]]></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>[cm,m,km]</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;"></p>
<table>
    <tbody>
        <tr>
            <td width="25%" style="text-align: center;">mm</td>
            <td width="25%" style="text-align: center;">cm</td>
            <td width="25%" style="text-align: center;">m</td>
            <td width="25%" style="text-align: center;">km</td>
        </tr>
        <tr>
            <td style="text-align: center;">{mm}</td>
            <td style="text-align: center;">{_0}</td>
            <td style="text-align: center;">{_1}</td>
            <td style="text-align: center;">{_2}</td>
        </tr>
    </tbody>
</table><br>
<p></p>]]></text>
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      <text>$course$/top/Default for MSII/Test #5/L39- Division Integers/L39- Vars with Integer equations</text>
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  <question type="formulas">
    <name>
      <text>L39 - Equation - Subtraction Signed Numbers (-+)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Calculate:</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><img src="@@PLUGINFILE@@/image%20%281%29.png" alt="" role="presentation" class="img-fluid"><br></p>
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    <tbody>
        <tr>
            <td width="30%">
                <h3>{A} - {B} = {var}</h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
            </td>
            <td>
            </td>
        </tr>
        <tr>
            <td>
                <h3></h3>
                <h3>{A} <span class="" style="color: rgb(255, 51, 102);"><strong>+</strong></span> <span class="" style="color: rgb(255, 51, 102);">{b}</span></h3>
            </td>
            <td></td>
            <td>
                <h3>Rewrite the subtraction as&nbsp;<br><strong><span class="" style="color: rgb(255, 51, 102);">Adding the opposite</span></strong></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{=A-B}</h3>
            </td>
            <td></td>
            <td>
                <h3><br></h3>
                <h3>Follow the rules of addition</h3>
                <h4>The signs are the same, find the sum&nbsp;</h4>
                <div class="editor-indent" style="margin-left: 30px;">
                    <p>The sum of {a} and {b} = {=abs(a+b)}</p>
                </div>
                <h4>Keep the sign.</h4>
                <div class="editor-indent" style="margin-left: 30px;">
                    <p>The answer is {signAns}</p>
                </div>
            </td>
        </tr>
    </tbody>
</table>
<h3>{var} = {=A-B}</h3><br>]]></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><![CDATA[a={1:10:1};
b={1:10:1};
var={"m","t","c","x","y","z"};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[b=(a==b)?b+1:b;
Sa=-1;
Sb=1;
A=Sa*a;
B=Sb*b;
larger=(a>b)?a:b;
signAns="negative";
m={-100:100};
t={-100:100};
c={-100:100};
x={-100:100};
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>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[Larger=(a>b)?(a):(b);
AnsSign=pick(a>b,["negative","positive"]);
NumSum = a+b;
Sum=A+B;]]></text>
 </vars1>
 <answer>
  <text>A-B</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 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[<h3 style="text-align: left;">{A} - {B} = {var}</h3><h3 style="text-align: left;">{var} = {_0}</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: 359960  -->
  <question type="formulas">
    <name>
      <text>L39- Equation (var on L) - Dividing Integers (fraction bar)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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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                                                       note that the size of the font can be defined in any units,
                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
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        var txt = $(".formulas_number").val();
        var size = $(".formulas_number").css('font-size');
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        var ctx = c.getContext("2d");
        ctx.font = size + " " + family;
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    </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[num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
var={"x","y","z","a","b","c"};
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);]]></text>
</varsrandom>
<varsglobal><text>a={-100:100};
b={-100:100};
c={-100:100};
x={-100:100};
y={-100:100};
z={-100:100};</text>
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<answernumbering><text>abc</text>
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  <text>0</text>
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 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
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 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
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A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
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Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",a/b);
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
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  <text>ans</text>
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<text><![CDATA[<h3><span>{var} = \(\frac{{A}}{{B}}\)</span></h3><h3><span>{var}={_0}</span></h3>]]></text>
 </subqtext>
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<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">{var} = \(\frac{{A}}{{B}}\)<h3>{var}={ans}</h3></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><p></p>]]></text>
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<text></text>
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<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359959  -->
  <question type="formulas">
    <name>
      <text>L39- Equation (var on R) - Dividing Integers (fraction bar)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>0.2500000</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[num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
var={"x","y","z","a","b","c"};
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);]]></text>
</varsrandom>
<varsglobal><text>a={-100:100};
b={-100:100};
c={-100:100};
x={-100:100};
y={-100:100};
z={-100:100};</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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  <text>0</text>
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  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",a/b);
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>ans</text>
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  <text><![CDATA[_err < 0.01]]></text>
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  <text>1</text>
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 <ruleid>
  <text>1</text>
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 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<h3><span>\(\frac{{A}}{{B}}\)= {var}</span></h3><h3><span>{var}={_0}</span></h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">\(\frac{{A}}{{B}}\)= {var}<h3>{var}={ans}</h3></span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><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: 359958  -->
  <question type="formulas">
    <name>
      <text>L39- Equation (var on right)- Dividing Integers</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>0.2500000</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[num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
var={"x","y","z","a","b","c"};]]></text>
</varsrandom>
<varsglobal><text>a={-100:100};
b={-100:100};
c={-100:100};
x={-100:100};
y={-100:100};
z={-100:100};</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",a/b);
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>ans</text>
 </answer>
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  <text></text>
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  <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[<h3><span>{A} ÷ {B} = {var}</span></h3><h3><span>{var} = {_0}</span></h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p>
<h3><span style="font-size: 1.64062rem;">
        <h3><span><h3>{var} = {A} ÷ {B}</h3><h3>{var} = {ans}</h3>
    </span></h3>
<p></p>
<h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3>
<div class="editor-indent" style="margin-left: 30px;">
    <h3>{Action}</h3>
</div>
<h3>{Work}</h3>
<h3>{SignAns}</h3><br>
<p></p></span></h3>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359965  -->
  <question type="formulas">
    <name>
      <text>L39- Equation -Subtraction Signed Numbers (--)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Calculate:</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><img src="@@PLUGINFILE@@/image%20%281%29.png" alt="" role="presentation" class="img-fluid"><br></p>
<p dir="ltr" style="text-align: left;"></p>
<table>
    <tbody>
        <tr>
            <td>
                <h3>{A} - {B} = {var}&nbsp;</h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
            </td>
            <td>
            </td>
        </tr>
        <tr>
            <td>
                <h3></h3>
                <h3>{A} <span class="" style="color: rgb(255, 51, 102);"><strong>+</strong></span> <span class="" style="color: rgb(255, 51, 102);">{b}</span></h3>
            </td>
            <td></td>
            <td>
                <h3>Rewrite the subtraction as&nbsp;<br><strong><span class="" style="color: rgb(255, 51, 102);">Adding the opposite</span></strong></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{=A-B}</h3>
            </td>
            <td></td>
            <td>
                <h3><br></h3>
                <h3>Follow the rules of addition</h3>
                <h4>The signs are different, take the difference&nbsp;</h4><div class="editor-indent" style="margin-left: 30px;"><p>The difference of {a} and {b} = {=abs(a-b)}</p></div><h4>Use the sign of the larger number.</h4><div class="editor-indent" style="margin-left: 30px;"><p>{larger} is larger, therefore the answer is {signAns}</p></div>
            </td>
        </tr>
    </tbody>
</table><h3>{var} = {=A-B}</h3><br>]]></text>
<file name="image (1).png" path="/" 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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><![CDATA[a={1:10:1};
b={1:10:1};
var={"m","t","c","x","y","z"};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[b=(a==b)?b+1:b;
Sa=-1;
Sb=-1;
A=Sa*a;
B=Sb*b;
larger=(a>b)?a:b;
signAns=pick(a>b,"positive","negative");
m={-100:100};
t={-100:100};
c={-100:100};
x={-100:100};
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>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[Larger=(a>b)?(a):(b);
AnsSign=pick(a>b,["negative","positive"]);
NumSum = a+b;
Sum=A+B;]]></text>
 </vars1>
 <answer>
  <text>A-B</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 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[<h3 style="text-align: left;">{A} - {B} = {var}</h3><h3 style="text-align: left;">{var} = {_0}</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: 359966  -->
  <question type="formulas">
    <name>
      <text>L39- Equation with Vars- Adding Signed Numbers (Random)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Calculate:</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><![CDATA[a={1:10:1};
b={1:10:1};
Sa={-1,1};
Sb={-1,1};
var={"x","y","z","t","s"};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[A=Sa*a;
B=Sb*b;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Take the difference.<br>Use the sign of the larger number.","Add the numbers<br>Keep the sign."]);
Work=pick(Sa==Sb,[join("","The difference of ",a," and ",b," is ",abs(a-b)),join("","The sum of ",a," and ",b," is ",a+b)]);
SignAns=pick(A+B>0,"The answer is negative","The answer is Positive");
x={-100:100:1};
y={-100:100:1};
z={-100:100:1};
t={-100:100:1};
s={-100:100:1};

]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>A+B</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[<h3 style="text-align: left;">{A} + {B} = {var}</h3><h3 style="text-align: left;">{var} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><p></p><h3>{A} + {B} = {=A+B}</h3><h3>{var} = {=A+B}</h3><br><p></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: 359957  -->
  <question type="formulas">
    <name>
      <text>L39- Equation-(var on left) Dividing Integers</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>0.2500000</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[num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
var={"x","y","z","a","b","c"};]]></text>
</varsrandom>
<varsglobal><text>a={-100:100};
b={-100:100};
c={-100:100};
x={-100:100};
y={-100:100};
z={-100:100};</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text>#a</text>
 </placeholder>
 <answermark>
  <text>0.25</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[a=num1[0]*num2[0];
b=num2[0];
Sa=signA[0];
Sb=signB[0];
A=Sa*a;
B=Sb*b;
ans=A/B;
SignA=pick(Sa>0,["negative","positive"]);
SignB=pick(Sb>0,["negative","positive"]);
SameSigns = pick(Sa==Sb,["different","the same"]);
Action=pick(Sa==Sb,["Divide the numbers.<br>The sign of the answer is negative.","Divide the numbers<br>The sign of the answer is positive."]);
Work=join("","The quotient of ",a," and ",b," is ",a/b);
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
 </vars1>
 <answer>
  <text>ans</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[<h3><span>{var} = {A} ÷ {B}</span></h3><h3><span>{var} = {_0}</span></h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p>
<h3><span style="font-size: 1.64062rem;">
        <h3><span><h3>{var} = {A} ÷ {B}</h3><h3>{var} = {ans}</h3>
    </span></h3>
<p></p>
<h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3>
<div class="editor-indent" style="margin-left: 30px;">
    <h3>{Action}</h3>
</div>
<h3>{Work}</h3>
<h3>{SignAns}</h3><br>
<p></p></span></h3>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 359963  -->
  <question type="formulas">
    <name>
      <text>L39-equation-var L -Subtraction Signed Numbers (+-)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Calculate:</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;"><img src="@@PLUGINFILE@@/image%20%281%29.png" alt="" role="presentation" class="img-fluid"><br></p>
<p dir="ltr" style="text-align: left;"></p>
<table>
    <tbody>
        <tr>
            <td width="30%">
                <h3></h3>
                <h3>{A} - {B} = {var}</h3>&nbsp;
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
            </td>
            <td>
            </td>
        </tr>
        <tr>
            <td>
                <h3></h3>
                <h3>{A} <span class="" style="color: rgb(255, 51, 102);"><strong>+</strong></span> <span class="" style="color: rgb(255, 51, 102);">{b}</span></h3>
            </td>
            <td></td>
            <td>
                <h3>Rewrite the subtraction as&nbsp;<br><strong><span class="" style="color: rgb(255, 51, 102);">Adding the opposite</span></strong></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{=A-B}</h3>
            </td>
            <td></td>
            <td>
                <h3><br></h3>
                <h3>Follow the rules of addition</h3>
                <h4>The signs are the same, find the sum&nbsp;</h4>
                <div class="editor-indent" style="margin-left: 30px;">
                    <p>The sum of {a} and {b} = {=abs(a+b)}</p>
                </div>
                <h4>Keep the sign.</h4>
                <div class="editor-indent" style="margin-left: 30px;">
                    <p>The answer is {signAns}</p>
                </div>
            </td>
        </tr>
    </tbody>
</table>
<h3>{var} = {=A-B}</h3><br>]]></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><![CDATA[a={1:10:1};
b={1:10:1};
var={"m","t","c","x","y","z"};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[b=(a==b)?b+1:b;
Sa=1;
Sb=-1;
A=Sa*a;
B=Sb*b;
larger=(a>b)?a:b;
signAns="positive";
m={-100:100};
t={-100:100};
c={-100:100};
x={-100:100};
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>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[Larger=(a>b)?(a):(b);
AnsSign=pick(a>b,["negative","positive"]);
NumSum = a+b;
Sum=A+B;]]></text>
 </vars1>
 <answer>
  <text>A-B</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 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[<h3 style="text-align: left;">{A} - {B} = {var}</h3><h3 style="text-align: left;">{var} = {_0}</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: 359962  -->
  <question type="formulas">
    <name>
      <text>L39-Var on Left Multiplying Integers (parentheses)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</td>
  </tr>
  
</tbody></table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
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b={-100:100:1};
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<answernumbering><text>abc</text>
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Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
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<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">{var} = {A}({B})</span></h3><h3><span style="font-size: 1.64062rem;">{var} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><br><p></p>]]></text>
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<text></text>
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<!-- question: 359961  -->
  <question type="formulas">
    <name>
      <text>L39-Var on Right Multiplying Integers (parentheses)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</td>
  </tr>
  
</tbody></table>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
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                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
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      <text>Your answer is incorrect.</text>
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num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
var={"x","y","z","a","b","c"};]]></text>
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<answernumbering><text>abc</text>
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SignB=pick(Sb>0,["negative","positive"]);
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Work=join("","The product of ",a," and ",b," is ",abs(a*b));
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<text><![CDATA[<p dir="ltr" style="text-align: left;"></p>
<h3><span style="font-size: 1.64062rem;">{A}({B}) = {var}</span></h3>
<h3><span style="font-size: 1.64062rem;">{var} = {ans}</span><br></h3>
<p></p>
<h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3>
<div class="editor-indent" style="margin-left: 30px;">
    <h3>{Action}</h3>
</div>
<h3>{Work}</h3>
<h3>{SignAns}</h3>
<p></p>
<h3>{var} ={=A*B}</h3>]]></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 359972  -->
  <question type="formulas">
    <name>
      <text>L39-Var on Right Multiplying Integers (parentheses)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Calculate:</h3>
<table>
    <tbody>
        <tr>
            <td>
                {#a}</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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                                                      e.g. small, medium, xx-large, 150%, 1.25cm, 22px
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                                  sizeN              size of the font w/o px, e.g. '14'
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        var txt = $(".formulas_number").val();
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            newWidth();
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      <text></text>
    </generalfeedback>
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    <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[num1=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
num2=shuffle([1,2,3,4,5,6,7,8,9,10,10,1,2,3,4,5,6,7,8,9,10]);
signA=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
signB=shuffle([-1,-1,-1,-1,-1,1,1,1,1,1]);
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<answernumbering><text>abc</text>
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  <text>100</text>
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  <text>1</text>
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b=num2[0];
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B=Sb*b;
ans=A*B;
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SignB=pick(Sb>0,["negative","positive"]);
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Action=pick(Sa==Sb,["Multiply the numbers.<br>The sign of the answer is negative.","Multiply the numbers<br>The sign of the answer is positive."]);
Work=join("","The product of ",a," and ",b," is ",abs(a*b));
SignAns=pick(A*B>0,"The answer is negative","The answer is Positive");]]></text>
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  <text>A*B</text>
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  <text></text>
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<text><![CDATA[<h3 style="text-align: left;">{A}({B}) = {var}</h3><h3 style="text-align: left;">{var} = {_0}</h3>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><h3><span style="font-size: 1.64062rem;">{A}({B}) = {var}</span></h3><h3><span style="font-size: 1.64062rem;">{var} = {ans}</span><br></h3><p></p><h3>{A} is a {SignA} number.<br>{B} is a {SignB} number.<br>The sign of {a} and {b} are {SameSigns}.&nbsp;</h3><div class="editor-indent" style="margin-left: 30px;"><h3>{Action}</h3></div><h3>{Work}</h3><h3>{SignAns}</h3><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 #5/L39- Division Integers/L39- Algebraic Expressions with Integers</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 359987  -->
  <question type="formulas">
    <name>
      <text>a b - c (d - e) + f</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if a={a}, b={b}, and c = {f}</h3>
<h3 style="text-align: left;">ab<span style="font-size: 19.6875px;">&nbsp;-&nbsp;</span>&nbsp;{c}({d} - {e}) + c</h3>
<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 txt = $(".formulas_number").val();
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        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() {
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<tdp>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</tdp>
<table>
    <tbody>
      <tr>
        <td><h3>ab&nbsp;-&nbsp;&nbsp;{c}(<span>{d} - {e}</span>) + c</h3></td>
        <td></td>
        <td>Substitute the values of the variable:<br><h3>a={a}, b={b}, and c = {f}</h3></td>
        <td></td>
      </tr>
        <tr>
            <td>
                <h3>{a}({b}) -&nbsp;&nbsp;{c}(<span class="" style="color: rgb(255, 51, 102);">{d} - {e}</span>) + {f}</h3>

            </td>
            <td></td>
            <td>
                <h3><span>Parentheses:&nbsp; {d} - {e}</span></h3>
            </td>
            <td style="text-align: center;"><img src="@@PLUGINFILE@@/ooo-parentheses.png" alt="parentheses" width="201" height="57" role="presentation"></td>
        </tr>
        <tr>
            <td>
                <h3><span class="" style="color: rgb(51, 102, 255);">{a}({b})</span>&nbsp;-&nbsp;&nbsp;{c}({=d-e}) + {f}</h3>
            </td>
            <td>

            </td>
            <td>
                <h3><span class="" style="color: rgb(51, 102, 255);">
                        <h3><span class="" style="color: rgb(51, 51, 51);">Multiply&nbsp;</span>{a}({b})</h3>
                    </span></h3>
            </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>{=a*b}&nbsp;-&nbsp;&nbsp;<span class="" style="color: rgb(51, 255, 102);">{c}({=d-e})</span> + {f}</h3>

            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>
                <h3>Multiply <span class="" style="color: rgb(51, 255, 102);">{c}({=d-e})</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><span class="" style="color: rgb(255, 204, 51);">{=a*b}&nbsp;-&nbsp;&nbsp;{=c*(d-e)} </span>+ {f}</h3>

            </td>
            <td>

            </td>
            <td>
                <h3>Subtract&nbsp; <span class="" style="color: rgb(255, 204, 51);">{=a/b}&nbsp;- {=c*(d-e)}</span></h3>
            </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>
                <h3><span class="" style="color: rgb(204, 51, 255);">{=a*b-(c*(d-e))} </span><span class="" style="color: rgb(204, 51, 255);">+ {f}</span></h3>

            </td>
            <td></td>
            <td>
                <h3>Add <span class="" style="color: rgb(204, 51, 255);">{=a*b-(c*(d-e))} + {f}</span></h3>
            </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>
                <h3>{ans}</h3>
            </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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    <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>a={8:15:1};
b={5:10:1};
c={1:5:1};
d={1:5:1};
e={1:10:1};
f={1:10:1};</text>
</varsrandom>
<varsglobal><text>d=d+e;

ans = a*b - c*(d-e) + f;</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: 359988  -->
  <question type="formulas">
    <name>
      <text>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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    </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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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>
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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={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>

<!-- question: 359986  -->
  <question type="formulas">
    <name>
      <text>L39- a + b(c+d)</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} + {d})</h3>
<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
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</script>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <h3>{a} + {b}(<span class="" style="color: rgb(255, 51, 102);">{c} + {d}</span>)</h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>First simplify inside the parentheses<br>
                <h3><span>Add <span class="" style="color: rgb(255, 51, 102);">{c} + {d}</span></span></h3><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>
                <h3>{a} + <span class="" style="color: rgb(51, 102, 255);">{b}({=c+d})</span></h3>
            </td>
            <td></td><td><h3><span>Multiply {b}({=c+d})</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><span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></h3>
            </td>
            <td></td>
            <td>
                <h3>Add <span class="" style="color: rgb(51, 255, 102);">{a} + {=b*(c + d)}</span></h3>
            </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><h3>{ans}</h3></td>
            <td></td>
            <td></td>
            <td></td>
        </tr>
    </tbody>
</table>]]></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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</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={-11:11:1};
b={-11:11:1};
c={-11:11:1};
d={-11:11:1};</text>
</varsrandom>
<varsglobal><text>ans = a + b*(c+d);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
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 <placeholder>
  <text></text>
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  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
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 <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: 359989  -->
  <question type="formulas">
    <name>
      <text>N+fv1</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {=variable[1]} = {number}<br></h3>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
    <tbody>
        <tr>
            <td>
                <h3>{question}</h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>


                <h3>1.&nbsp; Substitute{=variable[1]} = {number}</h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3></h3><h3>{varNum} + <span class="" style="color: rgb(255, 51, 102);">{factor}({number})</span></h3></td>
            <td></td>
            <td>
                <h3>2.&nbsp; Multiply <span class="" style="color: rgb(255, 51, 102);">{factor} x {number}</span></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3></h3><h3><span class="" style="color: rgb(51, 102, 255);">{varNum} + {=factor*number}</span></h3></td>
            <td></td>

            <td>
                <h3>3.&nbsp;<span class="" style="color: rgb(51, 102, 255);"> Add</span></h3>
            </td>


        </tr>
        <tr>
            <td>
                <h3>{ans}</h3>
            </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[variable=shuffle(["a","b","c","d","f","m","n","p","s","r","t","x","y","z"]);
number1={8:21:1};
number2={8:21:1};
factor={2:8:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number1:number2;
varNum=(number1>number2)?number2:number1;
ans=factor*number+varNum;
question=join("",varNum," + ",factor,variable[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>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[<h3 style="text-align: left;">{question}</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: 359990  -->
  <question type="formulas">
    <name>
      <text>N-v</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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>{varNum}<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> = {varNum}&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=number-varNum}</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Subtract</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};
number2={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number1:number2;
varNum=(number1>number2)?number2:number1;
ans=number-varNum;
question=join("",number," - ",variable);]]></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[<h3 style="text-align: left;">{question}</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: 359991  -->
  <question type="formulas">
    <name>
      <text>Na+B</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {=variable[1]} = {number}<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[<table>
    <tbody>
        <tr>
            <td>
                <h3>{question}</h3>
            </td>
            <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</td>
            <td>


                <h3>1.&nbsp; Substitute{=variable[1]} = {number}</h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{factor}({number}) + {varNum}</h3>
            </td>
            <td></td>
            <td>
                <h3>2.&nbsp; Multiply {factor} x {number}</h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3>{=factor*number} + {varNum}</h3>
            </td>
            <td></td>

            <td>
                <h3>3.&nbsp; Add</h3>
            </td>


        </tr>
        <tr>
            <td>
                <h3>{=ans}</h3>
            </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[variable=shuffle(["a","b","c","d","f","m","n","p","s","r","t","x","y","z"]);
number1={8:21:1};
number2={8:21:1};
factor={2:8:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number1:number2;
varNum=(number1>number2)?number2:number1;
ans=factor*number+varNum;
question=join("",factor,variable[1]," + ",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>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[<h3 style="text-align: left;">{question}</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: 359992  -->
  <question type="formulas">
    <name>
      <text>Nv</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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>{number}<span class="" style="color: rgb(51, 102, 255);">({varNum})</span><span style="font-size: 1.64062rem;">&nbsp;</span></h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(51, 51, 51);">{variable}</span> = {varNum}</h3><h3>Place {varNum} in <span class="" style="color: rgb(51, 102, 255);">parentheses to show it is multiplication&nbsp;</span></h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum*number}</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Multiply</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"};
number={1:11:1};
varNum={1:11:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[ans=number*varNum;
question=join("",number,variable);]]></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[<h3 style="text-align: left;">{question}</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: 359993  -->
  <question type="formulas">
    <name>
      <text>Nv1 + v2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {=variable[1]} = {number}<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>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">&nbsp;</span><span class="" style="color: rgb(51, 102, 255);"><span class="" style="color: rgb(51, 51, 51);">{=variable[1]} = {number}</span></span></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3><span class="" style="color: rgb(255, 51, 102);">
                        <h3><span class="" style="color: rgb(51, 51, 51);"><span class="" style="color: rgb(255, 51, 102);">{factor}({number})</span> + </span><span class="" style="color: rgb(51, 51, 51);">{varNum}</span><span style="font-size: 1.64062rem; color: rgb(51, 51, 51);" class="">&nbsp;</span></h3>
                    </span></h3>
            </td>
            <td></td>
            <td>
                <h3>2.&nbsp; <span class="" style="color: rgb(255, 51, 102);">Multiply {factor} x {number}</span></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3><span class="" style="color: rgb(51, 102, 255);">{=factor*number} + {varNum}</span></h3>
            </td>
            <td></td>

            <td>
                <h3>3.&nbsp; <span class="" style="color: rgb(51, 102, 255);">Add</span></h3>
            </td>


        </tr>
        <tr>
            <td>
                <h3>{=ans}</h3>
            </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[variable=shuffle(["a","b","c","d","f","m","n","p","s","r","t","x","y","z"]);
number1={8:21:1};
number2={8:21:1};
factor={2:8:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number1:number2;
varNum=(number1>number2)?number2:number1;
ans=factor*number+varNum;
question=join("",factor,variable[1]," + ",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>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[<h3 style="text-align: left;">{question}</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: 359994  -->
  <question type="formulas">
    <name>
      <text>Nv1 - v2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {=variable[1]} = {number}<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>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">&nbsp;</span><span class="" style="color: rgb(51, 102, 255);"><span class="" style="color: rgb(51, 51, 51);">{=variable[1]} = {number}</span></span></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3><span class="" style="color: rgb(255, 51, 102);">
                        <h3><span class="" style="color: rgb(51, 51, 51);"><span class="" style="color: rgb(255, 51, 102);">{factor}({number})</span> - </span><span class="" style="color: rgb(51, 51, 51);">{varNum}</span><span style="font-size: 1.64062rem; color: rgb(51, 51, 51);" class="">&nbsp;</span></h3>
                    </span></h3>
            </td>
            <td></td>
            <td>
                <h3>2.&nbsp; <span class="" style="color: rgb(255, 51, 102);">Multiply {factor} x {number}</span></h3>
            </td>
        </tr>
        <tr>
            <td>
                <h3><span class="" style="color: rgb(51, 102, 255);">{=factor*number} - {varNum}</span></h3>
            </td>
            <td></td>

            <td>
                <h3>3.&nbsp; <span class="" style="color: rgb(51, 102, 255);">Subtract&nbsp;</span></h3>
            </td>


        </tr>
        <tr>
            <td>
                <h3>{=ans}</h3>
            </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[variable=shuffle(["a","b","c","d","f","m","n","p","s","r","t","x","y","z"]);
number1={8:21:1};
number2={8:21:1};
factor={2:8:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number1:number2;
varNum=(number1>number2)?number2:number1;
ans=factor*number-varNum;
question=join("",factor,variable[1]," - ",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>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[<h3 style="text-align: left;">{question}</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: 359995  -->
  <question type="formulas">
    <name>
      <text>v+N</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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);">{varNum}</span> + {number}</h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = {varNum}&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum+number}</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"};
number={1:21:1};
varNum={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[ans=number+varNum;
question=join("",variable," + ",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>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[<h3 style="text-align: left;">{question}</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: 359996  -->
  <question type="formulas">
    <name>
      <text>v-N</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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);">{varNum}</span> - {number}</h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = {varNum}&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum-number}</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Subtract</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};
number2={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number2:number1;
varNum=(number1>number2)?number1:number2;
ans=varNum-number;
question=join("",variable," - ",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>ans</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[<h3 style="text-align: left;">{question}</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: 360005  -->
  <question type="formulas">
    <name>
      <text>v-N</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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);">{varNum}</span> - {number}</h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = {varNum}&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum-number}</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Subtract</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};
number2={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number2:number1;
varNum=(number1>number2)?number1:number2;
ans=varNum-number;
question=join("",variable," - ",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>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[<h3 style="text-align: left;">{question}</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: 360006  -->
  <question type="formulas">
    <name>
      <text>v-N</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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);">{varNum}</span> - {number}</h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = {varNum}&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum-number}</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Subtract</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};
number2={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number2:number1;
varNum=(number1>number2)?number1:number2;
ans=varNum-number;
question=join("",variable," - ",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>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[<h3 style="text-align: left;">{question}</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: 360009  -->
  <question type="formulas">
    <name>
      <text>v-N</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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);">{varNum}</span> - {number}</h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = {varNum}&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum-number}</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Subtract</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};
number2={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number2:number1;
varNum=(number1>number2)?number1:number2;
ans=varNum-number;
question=join("",variable," - ",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>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[<h3 style="text-align: left;">{question}</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: 360010  -->
  <question type="formulas">
    <name>
      <text>v-N</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {variable} = {varNum}<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);">{varNum}</span> - {number}</h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{variable}</span> = {varNum}&nbsp;</h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum-number}</h3></td>
            <td></td>
            <td><h3>2.&nbsp; Subtract</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};
number2={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number2:number1;
varNum=(number1>number2)?number1:number2;
ans=number-varNum;
question=join("",variable," - ",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>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[<h3 style="text-align: left;">{question}</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: 359997  -->
  <question type="formulas">
    <name>
      <text>v1 + v2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {=variable[0]} = {varNum}, and {=variable[1]} = {number}</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);">{varNum}</span> + <span class="" style="color: rgb(51, 102, 255);">{number}</span></h3></td>
            <td></td>
            <td><h3>1.&nbsp; Substitute <span class="" style="color: rgb(255, 51, 102);">{=variable[0]}</span><span class="" style="color: rgb(255, 51, 102);"> = {varNum}</span>,&nbsp;</h3><h3>and <span class="" style="color: rgb(51, 102, 255);">{=variable[1]}</span><span class="" style="color: rgb(51, 102, 255);"> = {number}</span></h3></td><td></td>
        </tr>
        <tr>
            <td><h3>{=varNum+number}</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=shuffle(["a","b","c","d","f","m","n","p","s","r","t","x","y","z"]);
number={1:21:1};
varNum={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[ans=number+varNum;
question=join("",variable[0]," + ",variable[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>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[<h3 style="text-align: left;">{question}</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: 359998  -->
  <question type="formulas">
    <name>
      <text>v1 - v2</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<h3 style="text-align: left;">Evaluate the expression if {=variable[0]} = {varNum}, and {=variable[1]} = {number}<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);"><span class="" style="color: rgb(51, 102, 255);">{number}</span> - </span>{varNum}<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[0]}</span><span class="" style="color: rgb(255, 51, 102);"> = {varNum}</span>, and <span class="" style="color: rgb(51, 102, 255);">{=variable[1]} = {number}</span></h3>
            </td>
            <td></td>
        </tr>
        <tr>
            <td>
                <h3>{=number-varNum}</h3>
            </td>
            <td></td>
            <td>
                <h3>2.&nbsp; Subtract</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=shuffle(["a","b","c","d","f","m","n","p","s","r","t","x","y","z"]);
number1={1:21:1};
number2={1:21:1};]]></text>
</varsrandom>
<varsglobal><text><![CDATA[number=(number1>number2)?number1:number2;
varNum=(number1>number2)?number2:number1;
ans=number-varNum;
question=join("",variable[1]," - ",variable[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>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[<h3 style="text-align: left;">{question}</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: 0  -->
  <question type="category">
    <category>
      <text>$course$/top/Default for MSII/Test #5/L40- Classification of Triangles/L40- Classify Triangles by Sides</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360062  -->
  <question type="formulas">
    <name>
      <text>L40- Equilateral</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,1.2,-1.2], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [0,0], {name:'',fixed:true});
    var tC=board.create('text',[0,-0.07,"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[theta={20:340:1};
fillC={"red","orange","green","black","blue","aqua","pink","maroon","purple"};
factor={5:50:1};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[#determine if isosceles or equilateral
difference=60;
s=theta;
Ya=sin(s*(pi()) /180);
Xa=cos(s*(pi()) /180);

t=theta-difference;
t=(t<0)?360+t:t;
Yb=sin(t*(pi()) /180);
Xb=cos(t*(pi()) /180);

disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=factor;
disBC=factor;

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=1;
ans=(theta==60)?2:ans;
ans=(difference==60)?2:ans;]]></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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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: 360061  -->
  <question type="formulas">
    <name>
      <text>L40- Isosceles Triangle (maybe equi)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,1.2,-1.2], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [0,0], {name:'',fixed:true});
    var tC=board.create('text',[0,-0.07,"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[theta={20:340:1};
difference={40:140:1};
factor={5:50:1};
fillC={"red","blue","green","orange","black","pink","maroon","yellow","aqua","purple"};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[#determine if isosceles or equilateral

s=theta;
Ya=sin(s*(pi()) /180);
Xa=cos(s*(pi()) /180);

t=theta-difference;
t=(t<0)?360+t:t;
Yb=sin(t*(pi()) /180);
Xb=cos(t*(pi()) /180);

disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=factor;
disBC=factor;

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=1;
ans=(theta==60)?2:ans;
ans=(difference==60)?2:ans;]]></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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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: 360063  -->
  <question type="formulas">
    <name>
      <text>L40- scalene (maybe isosc-equi)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle using the lengths of the sides.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-10,10,10,-10], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [{Xc},{Yc}], {name:'',fixed:true});
    var tC=board.create('text',[{Xc},{Yc},"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[Xa={-10:10};
Ya={-10:10};
Xb={-10:10};
Yb={-10:10};
Xc={-10:10};
Yc={-10:10};
factor={.1:2:.1};
fillC={"red","blue","green","orange","black","pink","maroon","yellow","aqua","purple"};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[slopeCB=(Yc-Yb)/(Xc=Xb);
slopeAC=(Ya-Yc)/(Xa=Xc);
Xc=(abs(slopeCB-slopeAC)<.1)?Xc+1:Xc;







disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=round(factor*pow((pow(Xa-Xc,2)+pow(Ya-Yc,2)),2),0);
disBC=round(factor*pow((pow(Xc-Xb,2)+pow(Yc-Yb,2)),2),0);

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=0;
ans=(disAC==disAB)?ans+1:ans;
ans=(disAC==disBC)?ans+1:ans;
ans=(disBC==disAB)?ans+1:ans;
ans=pick(ans,0,1,2,2);]]></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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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: 360060  -->
  <question type="formulas">
    <name>
      <text>L40-Isosceles-Q1</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Given Triangle ABC, AB = {ABround}, AC={AC}, and BC={BC}</p>
<p dir="ltr" style="text-align: left;">Classify the triangle by its sides.</p>

<jsxgraph width="300" height="300">
    var board=JXG.JSXGraph.initBoard(BOARDID,{axis:false,grid:false,boundingbox:[-.9,.9,.2,-.2], showCopyright:false, showNavigation:false}); var pA=board.create('point',[{Xa},{Ya}],{name:'A',fixed:true}); var pB=board.create('point',[0,0],{name:'B',fixed:true});
    var pC=board.create('point',[{Xc},{Yc}],{name:'',fixed:true}); var tC=board.create('text',[{Xc}+.01,{Yc}-.01,"C"],{anchorX:'left',anchorY:'top'}); var lineAB =board.create('line',[pA,pB],{straightFirst:false,straightLast:false}); var lineBC =board.create('line',[pB,pC],{straightFirst:false,straightLast:false});
    var lineAC =board.create('line',[pA,pC],{straightFirst:false,straightLast:false});&nbsp; var tAC=board.create('text',[{Xa}-.07,{Ya}/2,"{AC}"],{anchorX:'right',fontSize:20}); var tBC=board.create('text',[{Xc}/2,-.06,"{BC}"],{anchorX:'left',fontSize:20});
    var tAB=board.create('text',[{Xa}/2,{Ya}/2+.11,"{ABround}"],{anchorX:'left',anchorY:'top',fontSize:20}); var tangB=board.create('text',[-.05,.03,"45"],{anchorX:'right',color:'#0000ff'});
</jsxgraph>]]></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>X={1:10:1};
rand=shuffle([0,1,2]);</text>
</varsrandom>
<varsglobal><text><![CDATA[AC=X;
BC=X;
AB=X*sqrt(2);
ABround=round(AB,2);
Xa=-sqrt(2)/2;
Ya=sqrt(2)/2;
Xc=-sqrt(2)/2;
Yc=0;
AC2=AC*AC;
BC2=BC*BC;
AC2PBC2=AC2+BC2;
choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
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  <text>1</text>
 </answermark>
 <answertype>
  <text>100</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>0</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text>rand[_0]=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;">Triangle ABC:&nbsp; {_0:choice:MCE} triangle</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[Two sides of triangle ABC are equal in measure.<br><br>scalene triangle:&nbsp; none of the sides are equal in measure<br>isosceles triangle:&nbsp; two sides are equal in measure<br>equilateral triangle: all three sides are equal in measure<br><br>The triangle is an isosceles triangle<br>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360064  -->
  <question type="formulas">
    <name>
      <text>L40-scalene Triangle (maybe equi) angles</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC<br>&nbsp;AC={disAC} {units}, BC={disBC} {units}, and AB ={disAB} {units}
<br>Classify the triangle.
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{ axis:false,grid:false, boundingbox: [-1.2,1.2,1.2,-1.2], showCopyright: false, showNavigation: false });
    var pC= board.create('point', [{Xc},{Yc}], {name:'',fixed:true});
    var tC=board.create('text',[{Xc},{Yc},"C"],{fixed:true});

    var pA=board.create('point',[{Xa},{Ya}],{name:'',fixed:true});
    var tA=board.create('text',[{Xa},{Ya},"A"],{fixed:true});

    var pB=board.create('point',[{Xb},{Yb}],{name:'',fixed:true});
    var tB=board.create('text',[{Xb},{Yb},"B"],{fixed:true});

    var poly=board.create('polygon',[pA,pB,pC],{fillColor:'{fillC}'});
</jsxgraph>]]></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><![CDATA[theta={60:120:1};
difference={60:120:1};
third={60:120:1};
factor={5:50:1};
fillC={"red","blue","green","orange","black","pink","maroon","yellow","aqua","purple"};
units={"mm","cm","m","km","inches","yards","feet"};
rand=shuffle([0,1,2]);]]></text>
</varsrandom>
<varsglobal><text><![CDATA[#determine if isosceles or equilateral

s=theta;
Ya=sin(s*(pi()) /180);
Xa=cos(s*(pi()) /180);

t=theta-difference;
t=(t<0)?360+t:t;
Yb=sin(t*(pi()) /180);
Xb=cos(t*(pi()) /180);

x=theta-difference-third;
x=(t<0)?360+x:x;
Yc=sin(x*(pi()) /180);
Xc=cos(x*(pi()) /180);

disAB=round(factor*pow((pow(Xa-Xb,2)+pow(Ya-Yb,2)),2),0);
disAC=round(factor*pow((pow(Xa-Xc,2)+pow(Ya-Yc,2)),2),0);
disBC=round(factor*pow((pow(Xc-Xb,2)+pow(Yc-Yb,2)),2),0);

choices=["scalene","isosceles","equilateral"];
choice=[choices[rand[0]],choices[rand[1]],choices[rand[2]]];
ans=0;
ans=(disAC==disAB)?ans+1:ans;
ans=(disAC==disBC)?ans+1:ans;
ans=(disBC==disAB)?ans+1:ans;
]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
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  <text></text>
 </placeholder>
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  <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>rand[_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[<p dir="ltr" style="text-align: left;">Triange ABC:&nbsp; {_0:choice: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 #5/L40- Classification of Triangles/L40-Classify TRiangles by Angles</text>
    </category>
    <info format="html">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 360072  -->
  <question type="formulas">
    <name>
      <text>L40 - classify angles  triangle-missing angle C</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Triangle ABC is not drawn to scale.<br>Given: Triangle ABC 
<br>\(\angle\)A = {a} 
<br>\(\angle\)B = {b}
<br>Find:&nbsp;\(\angle\)C&nbsp;<br>
<jsxgraph width="300" height="300">
    var board = JXG.JSXGraph.initBoard(BOARDID,{axis:false,grid:false,showNavigation:false,showCopyright:false,boundingbox:[-.2,1.2,1.2,-1.2]}); var pA=board.create('point',[0,0],{size:1,name:'',fixed:true}); var tA=board.create('text',[-.01,-0.01,"A"],{anchorX:'right',anchorY:'top',fixed:true});
    var pB=board.create('point',[{Xb},{Yb}],{size:1,name:'B',anchorX:'right',anchorY:'bottom',fixed:true}); var pC=board.create('point',[{Xc},{Yc}],{size:1,name:'',anchorX:'right',anchorY:'top',fixed:true}); var tC=board.create('text',[{Xc},{Yc}-0.01,"C"],{anchorX:'right',anchorY:'top',fixed:true});
    var lineAB=board.create('line',[pA,pB],{fixed:true,straightFirst:false,straightLast:false}); var lineBC=board.create('line',[pB,pC],{fixed:true,straightFirst:false,straightLast:false}); var lineAC=board.create('line',[pA,pC],{fixed:true,straightFirst:false,straightLast:false});
    var tmA=board.create('text',[0,1.1,"Drag the Measurements to the triangle."],{anchorX:'left',fontSize:10}); var mA=board.create('text',[0,.9,"{a}"],{anchorX:'left',fontSize:20}); var mB=board.create('text',[0,.75,"{b}"],{anchorX:'left',fontSize:20});
    var mC=board.create('text',[0,.6,"x"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
  <tbody><tr>
    <td>
      \(\angle\) A +&nbsp;\(\angle\) B + \(\angle\) C = 180
    </td>
    <td>
      The sum of the angles of a triangle =&nbsp;\({180}^\circ\).
    </td>
  </tr>
  <tr>
    <td>{a} + {b} +&nbsp; \(\angle\) C = 180
    </td>
    <td>
    It is given that \(\angle\) A = {a} and \(\angle\) B = {b}
    </td>
    </tr>
 <tr>
   <td>\(\angle\) C&nbsp; +&nbsp;{aPb} = 180
   </td>
   <td>
   </td>
  </tr>
  <tr>
    <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<u> -{aPb}&nbsp; &nbsp;-{aPb}
</u>
    </td>
    <td>
    </td>
  </tr>
  <tr>
    <td>\(\angle\) C&nbsp; = {c}
  </td>
    <td>
    </td>
  </tr>
</tbody></table>]]></text>
    </generalfeedback>
    <defaultgrade>4.0000000</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>sPt={20:130:1};
s={18:70:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=sPt-s;
a=sPt;
b=90-s;
c=90-t;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
aPb=a+b;
choice=["acute","straight","obtuse","right"];
angA=(a<90)?0:((a>90)?2:3);
angC=(c<90)?0:((c>90)?2:3);
angB=(b<90)?0:((b>90)?2:3);]]></text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
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  <text>1</text>
 </answermark>
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 </answertype>
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  <text>1</text>
 </numbox>
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  <text></text>
 </vars1>
 <answer>
  <text>c</text>
 </answer>
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  <text></text>
 </vars2>
 <correctness>
  <text>_err == 0</text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">\(\angle\) C = {_0}</p>]]></text>
 </subqtext>
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<text></text>
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<text></text>
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<text></text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;A:&nbsp; {_0:choice:MCE} angle.</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;A = {a}</p><p dir="ltr" style="text-align: left;">&lt;A: {=choice[angA]} angle.</p>]]></text>
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<text></text>
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<text></text>
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<text></text>
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<answers>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;B:&nbsp; {_0:choice:MCE} angle</p>]]></text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">&lt;B = {b}</p><p dir="ltr">&lt;B: {=choice[angB]} angle.</p><br><p></p>]]></text>
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<text></text>
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<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">&lt;C:&nbsp; {_0:choice:MCE} angle</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><p dir="ltr">&lt;C = {c}</p><p dir="ltr">&lt;C: {=choice[angC]} angle.</p><br><p></p>]]></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: 360068  -->
  <question type="formulas">
    <name>
      <text>L40 - right triangle alg expr find angs</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[\(\angle\)B is a right angle.<br>\(\angle\)C ={s}°.<br>Find the measure of&nbsp; \(\angle\)A, then classify the triangle by its angles.<br>
<p></p>
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<br>
<h5>Click and drag the text labels if you are unable to read them.</h5>]]></text>
    </questiontext>
    <generalfeedback format="html">
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    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
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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>s={35:75:1};
X={-10:10:1};
a={2:15:1};
c={2:12:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=90-s;
ax=a*X;
cx=c*X;
b=s-ax;
d=t-cx;
aPc=a+c;
bPd=b+d;
axPb=ax+b;
cxPd=cx+d;
ninetyMbPd=90-bPd;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);
choice=["acute triangle","obtuse triangle","right triangle"];]]></text>
</varsglobal>
<answernumbering><text>abc</text>
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<text><![CDATA[<strong>\(\angle\)CAB= {_0}°<br></strong><br>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[The sum of the angles of a triangle =&nbsp;\({180}^\circ\).<br>It is given that \(\angle\) B = \({90}^\circ\) and &nbsp;\(\angle\) C = \({{s}}^\circ\).<br><br>The drawing states that&nbsp;\(\angle\) A = \({x}^\circ\)<br><br>
<table>
    <tbody>
        <tr>
            <td width="40%">x + {s} + 90 = \({180}^\circ\)
            </td>
            <td></td>
            <td>
                The sum of the angles = \({180}^\circ\)
            </td>
        </tr>
        <tr>
            <td>x + {=s+90}&nbsp;= \({180}^\circ\)</td>
            <td></td>
            <td>Simplify on the left side of the equation</td>
        </tr>
        <tr>
            <td>&nbsp; &nbsp;- {=s+90}&nbsp;= - {=s+90}&nbsp;<br></td>
            <td></td>
            <td>Subtract&nbsp;{=s+90} from both sides</td>
        </tr>
        <tr>
            <td>x = \({{t}}^\circ\)</td>
            <td></td>
            <td>\(\angle\) A = \({{t}}^\circ\)
            </td>
        </tr>
    </tbody>
</table><br><br>]]></text>
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 <correctfeedback format="html">
<text></text>
 </correctfeedback>
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<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
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  <text>1</text>
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 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">The triangle is classified as a {_0:choice:MCE}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">A triangle that has a right angle is classified as a <strong>right triangle</strong>.</p>]]></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
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<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 360069  -->
  <question type="formulas">
    <name>
      <text>L40 - right triangle measurement</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[\(\angle\)ABC is a right angle.<br>Find the measure of \(\angle\)ACB given that \(\angle\)CAB={s}°
<br>
<p></p>
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</jsxgraph>
<br>
<h5>Click and drag the text labels if you are unable to read them.</h5>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[The sum of the angles of a triangle =&nbsp;\({180}^\circ\).<br>It is given that \(\angle\) B = \({90}^\circ\).<br>180-90 = 90.<br>The sum of the two unknown angles = \({90}^\circ\)<br>{s} + x = \({90}^\circ\)<br><u> -{s}&nbsp; &nbsp; &nbsp; &nbsp; -{s}</u><br>x= {t}]]></text>
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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>s={35:75:1};
X={-10:10:1};
a={2:15:1};
c={2:12:1};</text>
</varsrandom>
<varsglobal><text>t=90-s;
ax=a*X;
cx=c*X;
b=s-ax;
d=t-cx;
aPc=a+c;
bPd=b+d;
axPb=ax+b;
cxPd=cx+d;
ninetyMbPd=90-bPd;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text><![CDATA[<strong>\(\angle\)ACB={_0}&nbsp;°</strong><br>]]></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: 360070  -->
  <question type="formulas">
    <name>
      <text>L40 - rt tri alg expr find angs-QII</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[\(\angle\)B is a right angle.<br>\(\angle\)C = {t}°<br>Find the measure of \(\angle\)A&nbsp;&nbsp;<br><br>
<p></p>
<jsxgraph width="300" height="300">
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</jsxgraph>
<br>
<h5>Click and drag the text labels if you are unable to read them.</h5>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[The sum of the angles of a triangle =&nbsp;\({180}^\circ\).<br>It is given that \(\angle\) B = \({90}^\circ\) and \(\angle\)C = {t}°.<br><br><table>
    <tbody>
        <tr>
            <td>x + {t} + 90 = \({180}^\circ\)
            </td>
            <td></td>
            <td>
                The sum of the angles = \({180}^\circ\)
            </td>
        </tr>
        <tr>
            <td>x + {=90+t} = 180</td>
            <td></td>
            <td>Add {t} + 90</td>
        </tr>
        <tr>
            <td>-{=90+t}&nbsp; &nbsp;&nbsp;-{=90+t}</td>
            <td></td>
            <td>Subtract&nbsp;-{=90+t} from both sides</td>
        </tr>
        <tr>
            <td>x = {s}</td>
            <td></td>
            <td>Simplify</td>
        </tr>
        <tr>
            <td>&nbsp; &nbsp; &nbsp; &nbsp;\(\angle\)A = {s}°.</td><td></td><td></td></tr></tbody></table>]]></text>
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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>s={35:75:1};
X={-10:10:1};
a={2:15:1};
c={2:12:1};</text>
</varsrandom>
<varsglobal><text>t=90-s;
ax=a*X;
cx=c*X;
b=s-ax;
d=t-cx;
aPc=a+c;
bPd=b+d;
axPb=ax+b;
cxPd=cx+d;
ninetyMbPd=90-bPd;
Ym=sin(s*(pi()) /180);
Xm=cos(s*(pi()) /180);</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
<answers>
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  <text>0</text>
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  <text>1</text>
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  <text>s</text>
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 <subqtext format="html">
<text><![CDATA[<strong>\(\angle\)A= {_0} °</strong><br>]]></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: 360073  -->
  <question type="formulas">
    <name>
      <text>L40-  angle-classify  triangle-missing angle-A</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr"></p>Given: Triangle ABC 
<br>\(\angle\)B = {b} 
<br>\(\angle\)C = {c}
<br>Find:&nbsp;\(\angle\)A, then classify the triangle<br>
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    var mC=board.create('text',[0,.6,"{c}"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text><![CDATA[<table>
  <tbody><tr>
    <td>
      \(\angle\) A +&nbsp;\(\angle\) B + \(\angle\) C = 180
    </td>
    <td>
      The sum of the angles of a triangle =&nbsp;\({180}^\circ\).
    </td>
  </tr>
  <tr>
    <td>\(\angle\) A + {b} +&nbsp; {c} = 180
    </td>
    <td>
    It is given that \(\angle\) B = {b} and \(\angle\) C = {c}
    </td>
    </tr>
 <tr>
   <td>\(\angle\) A&nbsp; +&nbsp;{bPc} = 180
   </td>
   <td>
   </td>
  </tr>
  <tr>
    <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<u> -{bPc}&nbsp; &nbsp;-{bPc}
</u>
    </td>
    <td>
    </td>
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  <tr>
    <td>\(\angle\) A&nbsp; = {a}
  </td>
    <td>
    </td>
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</tbody></table>]]></text>
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<varsrandom><text>sPt={20:130:1};
s={41:70:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=sPt-s;
a=sPt;
b=90-s;
c=90-t;

angleA=(a<90)?0:((a>90)?1:2);
angleB=(b<90)?0:((b>90)?1:2);
angleC=(c<90)?0:((c>90)?1:2);
ansChoice=angleA+angleB+angleC;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
bPc=b+c;
choice=["acute","obtuse","right"];]]></text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">\(\angle\) A = {_0}</p>]]></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>
 </incorrectfeedback>
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  <text>1</text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">The triangle is classified as a(n) {_0:choice:MCE} triangle</p><br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;"></p><br>]]></text>
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<text></text>
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<text></text>
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  </question>

<!-- question: 360074  -->
  <question type="formulas">
    <name>
      <text>L40-  classify Triangle</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr"></p>Given: Triangle ABC,&nbsp; \(\angle\)B = {b},&nbsp;\(\angle\)C = {c}, and&nbsp;&nbsp;\(\angle\)A = {a}<br>Classify the triangle<br>
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    var mC=board.create('text',[0,.6,"{c}"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></text>
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      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
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      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>sPt={20:130:1};
s={41:70:1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t=sPt-s;
a=sPt;
b=90-s;
c=90-t;

angleA=(a<90)?0:((a>90)?1:2);
angleB=(b<90)?0:((b>90)?1:2);
angleC=(c<90)?0:((c>90)?1:2);
ansChoice=angleA+angleB+angleC;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
bPc=b+c;
choice=["acute","obtuse","right"];]]></text>
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<answernumbering><text>abc</text>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">The triangle is classified as a(n) {_0:choice:MCE} triangle</p><br><p></p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[A triangle with three acute angles is an acute triangle.<br>A triangle with one obtuse angle is an obtuse triangle.<br>A triangle with one right angle is a right triangle.<br><br>Triangle ABC:&nbsp; {=choice[ansChoice]} triangle]]></text>
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</answers>
  </question>

<!-- question: 360071  -->
  <question type="formulas">
    <name>
      <text>L40-triangle-missing angle B</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[Given: Triangle ABC 
<br>\(\angle\)A = {a} 
<br>\(\angle\)C = {c}
<br>Find:&nbsp;\(\angle\)B&nbsp;<br>
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    var mC=board.create('text',[0,.6,"{c}"],{anchorX:'left',fontSize:20});
</jsxgraph>]]></text>
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    <generalfeedback format="html">
      <text><![CDATA[<table>
  <tbody><tr>
    <td>
      \(\angle\) A +&nbsp;\(\angle\) B + \(\angle\) C = 180
    </td>
    <td>
      The sum of the angles of a triangle =&nbsp;\({180}^\circ\).
    </td>
  </tr>
  <tr>
    <td>{a} + \(\angle\) B + {c} = 180
    </td>
    <td>
    It is given that \(\angle\) A = {a} and \(\angle\) C = {c}
    </td>
    </tr>
 <tr>
   <td>\(\angle\) B&nbsp; +&nbsp;{aPc} = 180
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   <td>
   </td>
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  <tr>
    <td>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<u> -{aPc}&nbsp; &nbsp;-{aPc}
</u>
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    <td>
    </td>
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  <tr>
    <td>\(\angle\) B&nbsp; = {b}
  </td>
    <td>
    </td>
  </tr>
</tbody></table>]]></text>
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      <text>Your answer is correct.</text>
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      <text>Your answer is partially correct.</text>
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<varsrandom><text>sPt={20:130:1};
s={18:70:1};</text>
</varsrandom>
<varsglobal><text>t=sPt-s;
a=sPt;
b=90-s;
c=90-t;
Yb=sin(s*(pi()) /180);
Xb=cos(s*(pi()) /180);
Yc=-1*sin(t*(pi()) /180);
Xc=cos(t*(pi()) /180);
aTextY=Yc/Xc*.04;
aPc=a+c;</text>
</varsglobal>
<answernumbering><text>abc</text>
</answernumbering>
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<text><![CDATA[<p dir="ltr" style="text-align: left;">\(\angle\) B = {_0}</p>]]></text>
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</quiz>