<snapdata remixID="15038309"><project name="Pseudocode Practice" app="Snap! 11.0.8, https://snap.berkeley.edu" version="2"><notes></notes><thumbnail>data:image/png;base64,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</thumbnail><scenes select="1"><scene name="Pseudocode Practice"><notes></notes><hidden></hidden><headers></headers><code></code><blocks><block-definition s="Calculate Variance Lists: %&apos;lists&apos; Mean: %&apos;Mean&apos;" type="reporter" category="variables"><header></header><code></code><translations></translations><inputs><input type="%l" initial="1"></input><input type="%s" initial="1"></input></inputs><script><block s="doDeclareVariables"><list><l>Variance</l></list></block><block s="doSetVar"><l>Count</l><l>0</l></block><block s="doSetVar"><l>SumSquaredDiffs</l><l>0</l></block><block s="doForEach"><l>number</l><block var="lists"/><script><block s="doSetVar"><l>Difference</l><block s="reportDifference"><block var="lists"/><block var="Mean"/></block></block><block s="doSetVar"><l>SquaredDiff</l><block s="reportVariadicProduct"><list><block var="Difference"/><block var="Difference"/></list></block></block><block s="doSetVar"><l>SumSquaredDiffs</l><block s="reportVariadicSum"><list><block var="SquaredDiff"/><block var="SumSquaredDiffs"/></list></block></block><block s="doSetVar"><l>Count</l><block s="reportVariadicSum"><list><block var="Count"/><l>1</l></list></block></block><block s="doSetVar"><l>Variance</l><block s="reportQuotient"><block var="SumSquaredDiffs"/><block var="Count"/></block></block></script></block><block s="doReport"><block var="Variance"/></block></script></block-definition></blocks><primitives></primitives><stage name="Stage" width="480" height="360" costume="0" color="255,255,255,1" tempo="60" threadsafe="false" penlog="false" volume="100" pan="0" lines="round" ternary="false" hyperops="true" codify="false" inheritance="true" sublistIDs="false" 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</pentrails><costumes><list struct="atomic" id="62"></list></costumes><sounds><list struct="atomic" id="63"></list></sounds><variables></variables><blocks></blocks><scripts></scripts><sprites select="1"><sprite name="Sprite" idx="1" x="0" y="0" heading="90" scale="1" volume="100" pan="0" rotation="1" draggable="true" costume="0" color="80,80,80,1" pen="tip" id="68"><costumes><list struct="atomic" id="69"></list></costumes><sounds><list struct="atomic" id="70"></list></sounds><blocks></blocks><variables></variables><scripts><script x="48" y="149"><custom-block s="Calculate Variance Lists: %l Mean: %s"><block s="reportNewList"><list><l>2</l><l>6</l><l>8</l><l>12</l><l>16</l></list></block><l>8.8</l></custom-block></script><script x="69" y="51.16666666666663"><block s="doSetVar"><l>SumSquaredDiffs</l><l>0</l></block></script><script x="85" y="206"><custom-block s="Calculate Variance Lists: %l Mean: %s"><block s="reportNewList"><list><l>3</l><l>7</l><l>10</l><l>23</l><l>31</l></list></block><l>14.8</l></custom-block></script><script x="67" y="295"><custom-block s="Calculate Variance Lists: %l Mean: %s"><block s="reportNewList"><list><l>5</l><l>10</l><l>22</l><l>36</l><l>47</l></list></block><l>24</l></custom-block></script></scripts></sprite><watcher var="Count" style="normal" x="10" y="10" color="243,118,29"/><watcher var="SquaredDiff" style="normal" x="330" y="1.00000399999999" color="243,118,29" extX="80" extY="70"/><watcher var="Difference" style="normal" x="224" y="1.000001999999995" color="243,118,29" extX="80" extY="70"/><watcher var="SumSquaredDiffs" style="normal" x="118" y="4.000005999999985" color="243,118,29" extX="80" extY="70"/><watcher var="Variance" style="normal" x="5" y="45.00000799999998" color="243,118,29"/></sprites></stage><variables><variable name="Count"><l>5</l></variable><variable name="Difference"><list struct="atomic" id="116">-19,-14,-2,12,23</list></variable><variable name="SquaredDiff"><list struct="atomic" id="117">361,196,4,144,529</list></variable><variable name="SumSquaredDiffs"><list struct="atomic" id="118">1805,980,20,720,2645</list></variable><variable name="Variance"><l>0</l></variable></variables></scene></scenes></project><media name="Pseudocode Practice" app="Snap! 11.0.8, https://snap.berkeley.edu" version="2"></media></snapdata>