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    <title>topic Distribution Nonconformance Statistics vs. Distribution Profiler in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Distribution-Nonconformance-Statistics-vs-Distribution-Profiler/m-p/544535#M76332</link>
    <description>&lt;P&gt;Hello JMP Community,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have a set of data that is best fit with a lognormal distribution. I cannot seem to find what is going on behind the scenes for the Nonconformance statistics vs. the 95% confidence intervals of the distribution profiler. When I run the capability analysis, I get a nonconformance table. Observed % is obvious in that my actual data population did not have any values below the LCL. What statistics are used for calculating the Expected Overall %, I assume it is using the lognormal distribution and making a judgement as to how well it fits the data; is it a 3 sigma approach or something? How is it calculated, and what useful information does it provide as opposed to the confidence intervals of the distribution profiler.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The confidence intervals I think are interpreted in the following manner: since I only have a LCL, I would look at the upper 95% confidence interval to make a statement along the lines of 'with 95% confidence one can expect 0.91% of values to fall below the LCL.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="gregpearce_1-1663169824888.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/45442iC12369D425193D21/image-size/medium?v=v2&amp;amp;px=400" role="button" title="gregpearce_1-1663169824888.png" alt="gregpearce_1-1663169824888.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you for any help on this!&lt;/P&gt;&lt;P&gt;Greg&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Sat, 10 Jun 2023 20:52:35 GMT</pubDate>
    <dc:creator>gregpearce</dc:creator>
    <dc:date>2023-06-10T20:52:35Z</dc:date>
    <item>
      <title>Distribution Nonconformance Statistics vs. Distribution Profiler</title>
      <link>https://community.jmp.com/t5/Discussions/Distribution-Nonconformance-Statistics-vs-Distribution-Profiler/m-p/544535#M76332</link>
      <description>&lt;P&gt;Hello JMP Community,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have a set of data that is best fit with a lognormal distribution. I cannot seem to find what is going on behind the scenes for the Nonconformance statistics vs. the 95% confidence intervals of the distribution profiler. When I run the capability analysis, I get a nonconformance table. Observed % is obvious in that my actual data population did not have any values below the LCL. What statistics are used for calculating the Expected Overall %, I assume it is using the lognormal distribution and making a judgement as to how well it fits the data; is it a 3 sigma approach or something? How is it calculated, and what useful information does it provide as opposed to the confidence intervals of the distribution profiler.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The confidence intervals I think are interpreted in the following manner: since I only have a LCL, I would look at the upper 95% confidence interval to make a statement along the lines of 'with 95% confidence one can expect 0.91% of values to fall below the LCL.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-inline" image-alt="gregpearce_1-1663169824888.png" style="width: 400px;"&gt;&lt;img src="https://community.jmp.com/t5/image/serverpage/image-id/45442iC12369D425193D21/image-size/medium?v=v2&amp;amp;px=400" role="button" title="gregpearce_1-1663169824888.png" alt="gregpearce_1-1663169824888.png" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you for any help on this!&lt;/P&gt;&lt;P&gt;Greg&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 10 Jun 2023 20:52:35 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Distribution-Nonconformance-Statistics-vs-Distribution-Profiler/m-p/544535#M76332</guid>
      <dc:creator>gregpearce</dc:creator>
      <dc:date>2023-06-10T20:52:35Z</dc:date>
    </item>
    <item>
      <title>Re: Distribution Nonconformance Statistics vs. Distribution Profiler</title>
      <link>https://community.jmp.com/t5/Discussions/Distribution-Nonconformance-Statistics-vs-Distribution-Profiler/m-p/544929#M76352</link>
      <description>&lt;P&gt;The difference between Observed and Expected is that Observed looks at your data (in the table) and Expected calculates % of LogNormal Curve below LSL. So one is describing the sample and one is predicting HVM from the fitted model.&lt;/P&gt;&lt;P&gt;Capability analysis answers the question: How good is this product at meeting Spec limits!&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The CI on the curve of predicition profiler says something about the certainty of your predicted probaility (of whatever your response is). So at 50000 Impedance/2 you predict a probability of 0.0003 (based on the sample) with a 95% certainty of the HVM value being somewhere between&amp;nbsp; 4.4e-6 and 0.009.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;So in short they are two very different pieces of information!&lt;/P&gt;</description>
      <pubDate>Thu, 15 Sep 2022 08:04:23 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Distribution-Nonconformance-Statistics-vs-Distribution-Profiler/m-p/544929#M76352</guid>
      <dc:creator>pauldeen</dc:creator>
      <dc:date>2022-09-15T08:04:23Z</dc:date>
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