<snapdata remixID="8579793"><project name="LS Regression" app="Snap! 5.1, http://snap.berkeley.edu" version="1"><notes></notes><thumbnail>data:image/png;base64,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</thumbnail><stage name="Stage" width="480" height="360" costume="0" color="255,255,255,1" tempo="60" threadsafe="false" volume="100" pan="0" lines="round" ternary="false" codify="false" inheritance="true" sublistIDs="false" scheduled="false" id="1"><pentrails>data:image/png;base64,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</pentrails><costumes><list struct="atomic" id="2"></list></costumes><sounds><list struct="atomic" id="3"></list></sounds><variables></variables><blocks></blocks><scripts></scripts><sprites><sprite name="Sprite" idx="1" x="-244.63052433966618" y="-175.0173735866552" heading="234.6304044636541" scale="1" volume="100" pan="0" rotation="1" draggable="true" hidden="true" costume="2" color="80,80,80,1" pen="tip" id="8"><costumes><list id="9"><item><costume name="Untitled" center-x="8" center-y="7.5" image="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAPCAYAAADtc08vAAAA/0lEQVQ4T92Sz0oCURTGf+eCvcDcBH2IoAxyaOXKjUKUD1E9QG1atukFyoewEHRhq1bmBP2BHiLBxhdQuCdGm2EYBG2W3eV3vu93z718woqjYF4suw5K0djA+CDkQ8Bl7ZIWAkvNwSlwBGxlzDOga6BdDXmKZwlgaLkVOFu1UVZTuDsMOY/0BWC0TUeVk03Cyc3Cvf9NS4YeFyLc/CUce1W5lGdL9LZCHgAwjwCaM7yI/QuAxwChnusflEcJLBUHr3kABvaXRfI4VqETF2sDmIrS8qc8JFUOiuw4xzXQXAPoGcNVdcJnUuV0YGTZU2gIVBTKv6YvhTeBvh/ynvb/AGqtRTaK7XspAAAAAElFTkSuQmCC" id="10"/></item><item><costume name="Untitled(2)" center-x="4" center-y="4.5" image="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAJCAYAAAAPU20uAAAAhUlEQVQoU2NkgIIPXAwmjH8ZrEHc/8wMRwW+MZwBsRlBxGcOhhn/GRjSYYqhEjN5fzBkMH7gYKhiYmBoRZaEsf8xMFQzfuJg+I9NEiZGHQX7GBgYHHFYs5/xIyeDGeN/hpPYFPxnZDAHe/MDF4MR01+GSgZGBiewwv8M+/4xM7QLfGM4BwA+aCNPVi8/XAAAAABJRU5ErkJggg==" id="11"/></item></list></costumes><sounds><list struct="atomic" id="12"></list></sounds><blocks></blocks><variables></variables><scripts><script x="10" y="21"><block s="receiveGo"></block><block s="hide"></block><custom-block s="Clear Blocks"></custom-block><custom-block s="Coordinate system steps %s"><l>500</l></custom-block><block s="doSetVar"><l>Data</l><block s="reportNewList"><list><block s="reportNewList"><list><l>10</l><l>5</l></list></block><block s="reportNewList"><list><l>50</l><l>32</l></list></block><block s="reportNewList"><list><l>100</l><l>74</l></list></block><block s="reportNewList"><list><l>130</l><l>81</l></list></block><block s="reportNewList"><list><l>155</l><l>100</l></list></block><block s="reportNewList"><list><l>230</l><l>161</l></list></block><block s="reportNewList"><list><l>140</l><l>116</l></list></block></list></block><comment w="112.779296875" collapsed="true">List of (x,y) points.  </comment></block><custom-block s="Initial values"></custom-block><custom-block s="Calculate values"></custom-block><custom-block s="Points"></custom-block><custom-block s="Write equation"></custom-block><custom-block s="Line of best fit steps %s"><l>300</l></custom-block></script></scripts></sprite><watcher var="Data" style="normal" x="10" y="10" color="243,118,29" hidden="true"/><watcher var="y" style="normal" x="10" y="263.000004" color="243,118,29" hidden="true"/><watcher var="x^2" style="normal" x="147" y="183.999998" color="243,118,29" hidden="true"/><watcher var="number" style="normal" x="10" y="288" color="243,118,29" hidden="true"/><watcher var="xy" style="normal" x="251" y="105.999998" color="243,118,29" hidden="true"/><watcher var="N" style="normal" x="10" y="309.000002" color="243,118,29" hidden="true"/><watcher var="∑x" style="normal" x="7" y="7.999998000000005" color="243,118,29" hidden="true"/><watcher var="∑y" style="normal" x="84" y="7.999998000000005" color="243,118,29" hidden="true"/><watcher var="∑x^2" style="normal" x="161" y="8.000001999999995" color="243,118,29" hidden="true"/><watcher var="∑xy" style="normal" x="257" y="8.000001999999995" color="243,118,29" hidden="true"/><watcher var="y-intercept" style="normal" x="7" y="35.999998000000005" color="243,118,29" hidden="true"/><watcher var="slope" style="normal" x="161" y="37.00000399999999" color="243,118,29" hidden="true"/><watcher var="x" style="normal" x="55" y="244.000002" color="243,118,29" extX="80" extY="70" hidden="true"/></sprites></stage><hidden> bounceOffEdge</hidden><headers></headers><code></code><blocks><block-definition s="Clear Blocks" type="command" category="variables"><header></header><code></code><translations></translations><inputs></inputs><script><block s="gotoXY"><l>-200</l><l>0</l></block><block s="clear"></block><block s="doSetVar"><l>∑x^2</l><l>0</l></block><block s="doSetVar"><l>∑x</l><l>0</l></block><block s="doSetVar"><l>∑x</l><l>0</l></block><block s="doSetVar"><l>∑y</l><l>0</l></block><block s="doSetVar"><l>xy</l><l>0</l></block><block s="doSetVar"><l>x^2</l><l>0</l></block><block s="doSetVar"><l>∑xy</l><l>0</l></block><block s="doSetVar"><l>slope</l><l>0</l></block></script></block-definition><block-definition s="Initial values" type="command" category="variables"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doSetVar"><l>x^2</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>xy</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>x</l><block s="reportNewList"><list></list></block></block><block s="doForEach"><l>item</l><block var="Data"/><script><block s="doAddToList"><block s="reportListItem"><l>1</l><block var="item"/></block><block var="x"/></block></script></block><block s="doSetVar"><l>y</l><block s="reportNewList"><list></list></block></block><block s="doForEach"><l>item</l><block var="Data"/><script><block s="doAddToList"><block s="reportListItem"><l><option>last</option></l><block var="item"/></block><block var="y"/></block></script></block><block s="doSetVar"><l>xy</l><block s="reportNewList"><list></list></block></block><block s="doSetVar"><l>number</l><l>0</l></block><block s="doSetVar"><l>N</l><block s="reportListLength"><block var="x"/></block></block></script><scripts><script x="260" y="185.99999999999994"><block s="doSetVar"><l>x</l><block s="reportNewList"><list><l>10</l><l>50</l><l>100</l><l>130</l><l>155</l><l>230</l><l>140</l></list></block></block></script><script x="273" y="266"><block s="doSetVar"><l>y</l><block s="reportNewList"><list><l>5</l><l>32</l><l>74</l><l>81</l><l>100</l><l>161</l><l>116</l></list></block></block></script></scripts></block-definition><block-definition s="Calculate values" type="command" category="variables"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doForEach"><l>item</l><block var="x"/><script><block s="doSetVar"><l>∑x</l><block s="reportSum"><block var="item"/><block var="∑x"/></block></block></script></block><block s="doForEach"><l>item</l><block var="y"/><script><block s="doSetVar"><l>∑y</l><block s="reportSum"><block var="item"/><block var="∑y"/></block></block></script></block><block s="doForEach"><l>item</l><block var="x"/><script><block s="doAddToList"><block s="reportPower"><block var="item"/><l>2</l></block><block var="x^2"/></block></script></block><block s="doForEach"><l>item</l><block var="x^2"/><script><block s="doSetVar"><l>∑x^2</l><block s="reportSum"><block var="item"/><block var="∑x^2"/></block></block></script></block><block s="doRepeat"><block s="reportListLength"><block var="x"/></block><script><block s="doChangeVar"><l>number</l><l>1</l></block><block s="doAddToList"><block s="reportProduct"><block s="reportListItem"><block var="number"/><block var="x"/></block><block s="reportListItem"><block var="number"/><block var="y"/></block></block><block var="xy"/></block></script></block><block s="doForEach"><l>item</l><block var="xy"/><script><block s="doSetVar"><l>∑xy</l><block s="reportSum"><block var="item"/><block var="∑xy"/></block></block></script></block><block s="doSetVar"><l>slope</l><block s="reportQuotient"><block s="reportDifference"><block s="reportProduct"><block var="N"/><block var="∑xy"/></block><block s="reportProduct"><block var="∑x"/><block var="∑y"/></block></block><block s="reportDifference"><block s="reportProduct"><block var="N"/><block var="∑x^2"/></block><block s="reportPower"><block var="∑x"/><l>2</l></block></block></block></block><block s="doSetVar"><l>y-intercept</l><block s="reportQuotient"><block s="reportDifference"><block var="∑y"/><block s="reportProduct"><block var="slope"/><block var="∑x"/></block></block><block var="N"/></block></block></script></block-definition><block-definition s="Write equation" type="command" category="pen"><header></header><code></code><translations></translations><inputs></inputs><script><block s="gotoXY"><l>25</l><l>-25</l></block><block s="write"><block s="reportJoinWords"><list><l>y = </l><block s="reportQuotient"><block s="reportRound"><block s="reportProduct"><block var="slope"/><l>10000</l></block></block><l>10000</l></block><l>x</l><l> + </l><block s="reportQuotient"><block s="reportRound"><block s="reportProduct"><block var="y-intercept"/><l>10000</l></block></block><l>10000</l></block></list></block><l>15</l></block></script></block-definition><block-definition s="Coordinate system steps %&apos;steps&apos;" type="command" category="motion"><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="gotoXY"><l>0</l><l>0</l></block><block s="down"></block><block s="setHeading"><l>0</l></block><block s="forward"><block var="steps"/></block><block s="setHeading"><l>180</l></block><block s="forward"><block s="reportProduct"><l>2</l><block var="steps"/></block></block><block s="gotoXY"><l>0</l><l>0</l></block><block s="setHeading"><l>-90</l></block><block s="forward"><block var="steps"/></block><block s="setHeading"><l>90</l></block><block s="forward"><block s="reportProduct"><l>2</l><block var="steps"/></block></block><block s="gotoXY"><l>0</l><l>0</l></block><block s="up"></block></script></block-definition><block-definition s="Go to point: %&apos;point&apos;" type="command" category="motion"><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doGotoObject"><block var="point"/></block></script></block-definition><block-definition s="Y coordinate of point %&apos;point&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportListItem"><l><option>last</option></l><block var="point"/></block></block></script></block-definition><block-definition s="X coordinate of point %&apos;point&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%l"></input></inputs><script><block s="doReport"><block s="reportListItem"><l>1</l><block var="point"/></block></block></script></block-definition><block-definition s="point X: %&apos;X&apos; Y: %&apos;Y&apos;" type="reporter" category="operators"><header></header><code></code><translations></translations><inputs><input type="%n"></input><input type="%n"></input></inputs><script><block s="doReport"><block s="reportNewList"><list><block var="X"/><block var="Y"/></list></block></block></script></block-definition><block-definition s="Points" type="command" category="pen"><header></header><code></code><translations></translations><inputs></inputs><script><block s="doForEach"><l>item</l><block var="Data"/><script><custom-block s="Go to point: %l"><custom-block s="point X: %n Y: %n"><custom-block s="X coordinate of point %l"><block var="item"/></custom-block><custom-block s="Y coordinate of point %l"><block var="item"/></custom-block></custom-block></custom-block><block s="show"></block><block s="doStamp"></block><block s="hide"></block></script></block></script></block-definition><block-definition s="Line of best fit steps %&apos;steps&apos;" type="command" category="motion"><header></header><code></code><translations></translations><inputs><input type="%s"></input></inputs><script><block s="gotoXY"><l>0</l><block var="y-intercept"/></block><block s="down"></block><block s="setHeading"><block s="reportDifference"><l>90</l><block s="reportMonadic"><l><option>atan</option></l><block var="slope"/></block></block></block><block s="forward"><block var="steps"/></block><block s="turnLeft"><l>180</l></block><block s="forward"><block s="reportProduct"><l>2</l><block var="steps"/></block></block></script></block-definition></blocks><variables><variable name="Data"><list id="458"><item><list struct="atomic" id="459">10,5</list></item><item><list struct="atomic" id="460">50,32</list></item><item><list struct="atomic" id="461">100,74</list></item><item><list struct="atomic" id="462">130,81</list></item><item><list struct="atomic" id="463">155,100</list></item><item><list struct="atomic" id="464">230,161</list></item><item><list struct="atomic" id="465">140,116</list></item></list></variable><variable name="∑x^2"><l>126025</l></variable><variable name="x"><list struct="atomic" id="466">10,50,100,130,155,230,140</list></variable><variable name="y"><list struct="atomic" id="467">5,32,74,81,100,161,116</list></variable><variable name="∑x"><l>815</l></variable><variable name="∑y"><l>569</l></variable><variable name="xy"><list struct="atomic" id="468">50,1600,7400,10530,15500,37030,16240</list></variable><variable name="x^2"><list struct="atomic" id="469">100,2500,10000,16900,24025,52900,19600</list></variable><variable name="number"><l>7</l></variable><variable name="∑xy"><l>88350</l></variable><variable name="N"><l>7</l></variable><variable name="slope"><l>0.7098646478550126</l></variable><variable name="y-intercept"><l>-1.362812571690743</l></variable></variables></project><media name="LS Regression" app="Snap! 5.1, http://snap.berkeley.edu" version="1"></media></snapdata>