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    <title>topic Re: Outlier detection in SAS Procedures</title>
    <link>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59871#M16916</link>
    <description>just as an addition to above answers.....To find outliers with character data you can use PROC FREQ to find all the values of a particular character variable.&lt;BR /&gt;
To find outliers in Numeric data we can use  PROC Means.</description>
    <pubDate>Fri, 19 Feb 2010 17:24:40 GMT</pubDate>
    <dc:creator>SAPPER</dc:creator>
    <dc:date>2010-02-19T17:24:40Z</dc:date>
    <item>
      <title>Outlier detection</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59867#M16912</link>
      <description>Hi ,&lt;BR /&gt;
&lt;BR /&gt;
could you suggest soem useful commands and their interpretations if I want to find if there are any influential observations / outliers in my data.&lt;BR /&gt;
&lt;BR /&gt;
Kind  Regards ,&lt;BR /&gt;
markc</description>
      <pubDate>Fri, 19 Feb 2010 02:59:55 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59867#M16912</guid>
      <dc:creator>deleted_user</dc:creator>
      <dc:date>2010-02-19T02:59:55Z</dc:date>
    </item>
    <item>
      <title>Re: Outlier detection</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59868#M16913</link>
      <description>Hi:&lt;BR /&gt;
  To investigate and explore your data, PROC UNIVARIATE is a good overall procedure to start with:&lt;BR /&gt;
&lt;A href="http://support.sas.com/documentation/cdl/en/procstat/63032/HTML/default/procstat_univariate_sect008.htm" target="_blank"&gt;http://support.sas.com/documentation/cdl/en/procstat/63032/HTML/default/procstat_univariate_sect008.htm&lt;/A&gt;&lt;BR /&gt;
&lt;A href="http://support.sas.com/documentation/cdl/en/procstat/63032/HTML/default/procstat_univariate_sect003.htm" target="_blank"&gt;http://support.sas.com/documentation/cdl/en/procstat/63032/HTML/default/procstat_univariate_sect003.htm&lt;/A&gt;&lt;BR /&gt;
     &lt;BR /&gt;
cynthia</description>
      <pubDate>Fri, 19 Feb 2010 03:17:20 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59868#M16913</guid>
      <dc:creator>Cynthia_sas</dc:creator>
      <dc:date>2010-02-19T03:17:20Z</dc:date>
    </item>
    <item>
      <title>Re: Outlier detection</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59869#M16914</link>
      <description>Whether or not an observation is an outlier or influential observation (they are often thought of differently) is a function of your putative model.  The UNIVARIATE procedure that Cynthia mentioned will look at several different single variable distributions.&lt;BR /&gt;
&lt;BR /&gt;
All of the regression type statistical models in SAS 9.2 have very good ODS graphics to assist in outlier detection.  There is a section with each procedure describing the diagnostic models available in the ODS Graphics.</description>
      <pubDate>Fri, 19 Feb 2010 03:28:19 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59869#M16914</guid>
      <dc:creator>Doc_Duke</dc:creator>
      <dc:date>2010-02-19T03:28:19Z</dc:date>
    </item>
    <item>
      <title>Re: Outlier detection</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59870#M16915</link>
      <description>For the "interpretations" part of your question, I use the mean and standard deviation to identify thresholds for univariate outliers.&lt;BR /&gt;
&lt;BR /&gt;
For samples &amp;lt; 500, outliers are values that exceed [mean + or - 1.96 standard deviations].  This is equivalent to a 95% confidence interval.&lt;BR /&gt;
&lt;BR /&gt;
If 500 &amp;lt; n &amp;lt; 5,000, [mean + or - 2.576 standard deviations]... 99% CI.&lt;BR /&gt;
&lt;BR /&gt;
For n &amp;gt; 5,000, [mean + or - 3.291 standard deviations]... 99.9% CI.&lt;BR /&gt;
&lt;BR /&gt;
For multivariate outliers, I look at Cook's D &amp;amp; DFFits most often.&lt;BR /&gt;
&lt;BR /&gt;
Good luck,&lt;BR /&gt;
&lt;BR /&gt;
Parker</description>
      <pubDate>Fri, 19 Feb 2010 13:07:10 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59870#M16915</guid>
      <dc:creator>Parker</dc:creator>
      <dc:date>2010-02-19T13:07:10Z</dc:date>
    </item>
    <item>
      <title>Re: Outlier detection</title>
      <link>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59871#M16916</link>
      <description>just as an addition to above answers.....To find outliers with character data you can use PROC FREQ to find all the values of a particular character variable.&lt;BR /&gt;
To find outliers in Numeric data we can use  PROC Means.</description>
      <pubDate>Fri, 19 Feb 2010 17:24:40 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Procedures/Outlier-detection/m-p/59871#M16916</guid>
      <dc:creator>SAPPER</dc:creator>
      <dc:date>2010-02-19T17:24:40Z</dc:date>
    </item>
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