https://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&feed=atom&action=historySumSquaredErrors Command - Revision history2024-03-29T05:37:54ZRevision history for this page on the wikiMediaWiki 1.35.1https://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=56384&oldid=prevMathmum: command syntax: changed [ ] into ( )2017-10-12T08:24:08Z<p>command syntax: changed [ ] into ( )</p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly<del class="diffchange diffchange-inline">[</del>L,1<del class="diffchange diffchange-inline">]</del></code> and <code>g(x)=FitPoly(L,2)</code>. <code>SumSquaredErrors(L,f)</code> yields ''9'' and <code>SumSquaredErrors(L,g)</code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly<ins class="diffchange diffchange-inline">(</ins>L,1<ins class="diffchange diffchange-inline">)</ins></code> and <code>g(x)=FitPoly(L,2)</code>. <code>SumSquaredErrors(L,f)</code> yields ''9'' and <code>SumSquaredErrors(L,g)</code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td></tr>
</table>Mathmumhttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=56382&oldid=prevMathmum: command syntax: changed [ ] into ( )2017-10-12T08:23:38Z<p>command syntax: changed [ ] into ( )</p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly<del class="diffchange diffchange-inline">[</del>L,2<del class="diffchange diffchange-inline">]</del></code>. <code>SumSquaredErrors<del class="diffchange diffchange-inline">[</del>L,f<del class="diffchange diffchange-inline">]</del></code> yields ''9'' and <code>SumSquaredErrors<del class="diffchange diffchange-inline">[</del>L,g<del class="diffchange diffchange-inline">]</del></code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly<ins class="diffchange diffchange-inline">(</ins>L,2<ins class="diffchange diffchange-inline">)</ins></code>. <code>SumSquaredErrors<ins class="diffchange diffchange-inline">(</ins>L,f<ins class="diffchange diffchange-inline">)</ins></code> yields ''9'' and <code>SumSquaredErrors<ins class="diffchange diffchange-inline">(</ins>L,g<ins class="diffchange diffchange-inline">)</ins></code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td></tr>
</table>Mathmumhttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=55870&oldid=prevZbynek: Text replace - ";(.*)\[(.*)\]" to ";$1($2)"2017-10-07T15:17:21Z<p>Text replace - ";(.*)\[(.*)\]" to ";$1($2)"</p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>. <code>SumSquaredErrors[L,f]</code> yields ''9'' and <code>SumSquaredErrors[L,g]</code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>. <code>SumSquaredErrors[L,f]</code> yields ''9'' and <code>SumSquaredErrors[L,g]</code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td></tr>
</table>Zbynekhttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=49279&oldid=prevMarkus.winkler at 07:25, 24 August 20152015-08-24T07:25:38Z<p></p>
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<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <del class="diffchange diffchange-inline"><</del>List of Points>, <Function> ]</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <ins class="diffchange diffchange-inline">&lt;</ins>List of Points>, <Function> ]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>. <code>SumSquaredErrors[L,f]</code> yields ''9'' and <code>SumSquaredErrors[L,g]</code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <code><nowiki>L={(1, 2), (3, 5),(2, 2), (5, 2), (5, 5)}</nowiki></code> and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>. <code>SumSquaredErrors[L,f]</code> yields ''9'' and <code>SumSquaredErrors[L,g]</code> yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss).}}</div></td></tr>
</table>Markus.winklerhttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=49277&oldid=prevMarkus.winkler: changed example2015-08-24T07:18:58Z<p>changed example</p>
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<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <del class="diffchange diffchange-inline">&lt;</del>List of Points>, <Function> ]</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <ins class="diffchange diffchange-inline"><</ins>List of Points>, <Function> ]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points<del class="diffchange diffchange-inline">: </del>L={<del class="diffchange diffchange-inline">A</del>,<del class="diffchange diffchange-inline">B</del>,<del class="diffchange diffchange-inline">C</del>,<del class="diffchange diffchange-inline">D</del>,<del class="diffchange diffchange-inline">E</del>} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code><del class="diffchange diffchange-inline">, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: </del><code><del class="diffchange diffchange-inline">sse_f=</del>SumSquaredErrors[L,f]</code> and <code><del class="diffchange diffchange-inline">sse_g=</del>SumSquaredErrors[L,g]</code>.}}</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points <ins class="diffchange diffchange-inline"><code><nowiki></ins>L={<ins class="diffchange diffchange-inline">(1, 2), (3, 5),(2, 2)</ins>, <ins class="diffchange diffchange-inline">(5</ins>, <ins class="diffchange diffchange-inline">2)</ins>, <ins class="diffchange diffchange-inline">(5</ins>, <ins class="diffchange diffchange-inline">5)</ins>}<ins class="diffchange diffchange-inline"></nowiki></code> </ins> and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code><ins class="diffchange diffchange-inline">. </ins><code>SumSquaredErrors[L,f]</code> <ins class="diffchange diffchange-inline">yields ''9'' </ins>and <code>SumSquaredErrors[L,g]</code> <ins class="diffchange diffchange-inline">yields ''6.99'', and therefore we can see, that ''g(x)'' offers the best fit, in the sense of the least sum of squared errors (Gauss)</ins>.}}</div></td></tr>
</table>Markus.winklerhttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=49145&oldid=prevNoel Lambert at 19:31, 22 August 20152015-08-22T19:31:06Z<p></p>
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<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <del class="diffchange diffchange-inline"><</del>List of Points>, <Function> ]</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <ins class="diffchange diffchange-inline">&lt;</ins>List of Points>, <Function> ]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td></tr>
</table>Noel Lamberthttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=48467&oldid=prevMarkus.winkler at 09:34, 11 August 20152015-08-11T09:34:52Z<p></p>
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<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>{{command|statistics}} </div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <List of Points>, <Function> ]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <List of Points>, <Function> ]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td></tr>
</table>Markus.winklerhttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=46515&oldid=prevMarkus.winkler at 13:21, 28 July 20152015-07-28T13:21:52Z<p></p>
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<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><noinclude>{{Manual Page|version=<del class="diffchange diffchange-inline">4</del>.<del class="diffchange diffchange-inline">2</del>}}</noinclude></div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><noinclude>{{Manual Page|version=<ins class="diffchange diffchange-inline">5</ins>.<ins class="diffchange diffchange-inline">0</ins>}}</noinclude></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{command|statistics}} </div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{command|statistics}} </div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <List of Points>, <Function> ]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>;SumSquaredErrors[ <List of Points>, <Function> ]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td></tr>
</table>Markus.winklerhttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=42141&oldid=prevNoel Lambert: typo2014-10-27T17:40:21Z<p>typo</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 17:40, 27 October 2014</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{command|statistics}} </div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{command|statistics}} </div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>;<del class="diffchange diffchange-inline">SSumSquaredErrors</del>[ <List of Points>, <Function> ]</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>;<ins class="diffchange diffchange-inline">SumSquaredErrors</ins>[ <List of Points>, <Function> ]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td></tr>
</table>Noel Lamberthttps://wiki.geogebra.org/s/en/index.php?title=SumSquaredErrors_Command&diff=37348&oldid=prevMagdalenaSophieF at 12:58, 16 July 20132013-07-16T12:58:11Z<p></p>
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<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>;<del class="diffchange diffchange-inline">SumSquaredErrors</del>[ <List of Points>, <Function> ]</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>;<ins class="diffchange diffchange-inline">SSumSquaredErrors</ins>[ <List of Points>, <Function> ]</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>:Calculates the sum of squared errors, SSE, between the y-values of the points in the list and the function values of the x-values in the list.</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td><td class='diff-marker'>+</td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">:</ins>{{example|1= If we have a list of points: L={A,B,C,D,E} and have calculated for example: <code>f(x)=FitPoly[L,1]</code> and <code>g(x)=FitPoly[L,2]</code>, then it is possible to decide which of the two functions offers the best fit, in the sense of the least sum of squared errors (Gauss), by comparing: <code>sse_f=SumSquaredErrors[L,f]</code> and <code>sse_g=SumSquaredErrors[L,g]</code>.}}</div></td></tr>
</table>MagdalenaSophieF