<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: How does JMP adjust for p-value of Pearson Chi-Squared Value in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/231348#M45873</link>
    <description>&lt;P&gt;Thanks Tonya, that helps a lot.&amp;nbsp; Is there a way to control the bin size for ver. 15 and above?&amp;nbsp; In the example I have provided, I believe I wasn't giving the correct degrees of freedom for the Chi Squared Test in the alternate methods I was using.&lt;/P&gt;</description>
    <pubDate>Tue, 29 Oct 2019 19:17:05 GMT</pubDate>
    <dc:creator>zimmerj</dc:creator>
    <dc:date>2019-10-29T19:17:05Z</dc:date>
    <item>
      <title>How does JMP adjust for p-value of Pearson Chi-Squared Value</title>
      <link>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/229928#M45629</link>
      <description>&lt;P&gt;I'm doing a discrete fit between an observed count distribution and a Gamma-Poisson mixture.&amp;nbsp; However the Pearson Chi-Squared Goodness-of-fit statistics is returning a very high value for X2, but indicating an acceptable p-value.&lt;/P&gt;&lt;P&gt;In the example provided, X2 is 1222.58, which if inserted into a Chi Squared distribution would return a p-value of&amp;nbsp;7.552193e-268.&lt;/P&gt;&lt;P&gt;JMP returns a p-value of 0.1021.&lt;/P&gt;&lt;P&gt;Is there some adjustment that is done in JMP's calculation that would increase the value so much over a direct calculation?&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="Capture.PNG" style="width: 999px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/19813iB9F80905B7806B6B/image-size/large?v=v2&amp;amp;px=999" role="button" title="Capture.PNG" alt="Capture.PNG" /&gt;&lt;/span&gt;&lt;/P&gt;</description>
      <pubDate>Mon, 21 Oct 2019 21:04:24 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/229928#M45629</guid>
      <dc:creator>zimmerj</dc:creator>
      <dc:date>2019-10-21T21:04:24Z</dc:date>
    </item>
    <item>
      <title>Re: How does JMP adjust for p-value of Pearson Chi-Squared Value</title>
      <link>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/231070#M45828</link>
      <description>&lt;P&gt;The expected Chi Square under the null hypothesis is equal to the degrees of freedom.&amp;nbsp; Your degrees of freedom are high for this example, you have an N of 1162.&amp;nbsp; Therefore I am not surprised by the results.&lt;/P&gt;
&lt;P&gt;Most issues with the Pearson Goodness of Fit tests comes from the bin sizes.&lt;/P&gt;
&lt;P&gt;The Pearson Goodness of Fit test has changed for Version 15.&amp;nbsp; The problem with this test is that the bin size it not well defined.&amp;nbsp; For version 15, JMP makes sure there are at least 5 expected observations in each bin.&amp;nbsp; This way we satisfy that rule of thumb (the assumptions are towards the bottom). &amp;nbsp;&lt;A href="https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test" target="_self"&gt;https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test&lt;/A&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The last bin is the exception.&amp;nbsp; If it's expected count is less than 5, JMP does not worry about it.&lt;/P&gt;
&lt;P&gt;Previously, JMP treated every integer between the min and max as a bin.&amp;nbsp; This means there can be bins with zero observations and expections essentially zero.&lt;/P&gt;</description>
      <pubDate>Tue, 29 Oct 2019 11:59:23 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/231070#M45828</guid>
      <dc:creator>tonya_mauldin</dc:creator>
      <dc:date>2019-10-29T11:59:23Z</dc:date>
    </item>
    <item>
      <title>Re: How does JMP adjust for p-value of Pearson Chi-Squared Value</title>
      <link>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/231348#M45873</link>
      <description>&lt;P&gt;Thanks Tonya, that helps a lot.&amp;nbsp; Is there a way to control the bin size for ver. 15 and above?&amp;nbsp; In the example I have provided, I believe I wasn't giving the correct degrees of freedom for the Chi Squared Test in the alternate methods I was using.&lt;/P&gt;</description>
      <pubDate>Tue, 29 Oct 2019 19:17:05 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/231348#M45873</guid>
      <dc:creator>zimmerj</dc:creator>
      <dc:date>2019-10-29T19:17:05Z</dc:date>
    </item>
    <item>
      <title>Re: How does JMP adjust for p-value of Pearson Chi-Squared Value</title>
      <link>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/231413#M45891</link>
      <description>No, JMP Version 15 does not give the user control of the bin sizes that are used for the Pearson Goodness of Fit test.</description>
      <pubDate>Wed, 30 Oct 2019 11:48:55 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/How-does-JMP-adjust-for-p-value-of-Pearson-Chi-Squared-Value/m-p/231413#M45891</guid>
      <dc:creator>tonya_mauldin</dc:creator>
      <dc:date>2019-10-30T11:48:55Z</dc:date>
    </item>
  </channel>
</rss>

