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    <title>topic Re: Proc Univariate for simple standard problem in Statistical Procedures</title>
    <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497389#M25717</link>
    <description>&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/58513"&gt;@DmytroYermak&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;&amp;nbsp;for the beginners it is 'number of values within sigmas'&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;I object to this statement, as I don't see a need to do this computation 'number of values within sigmas' for two reasons:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;It does not really test normality&lt;/LI&gt;
&lt;LI&gt;There are better tests of normality that are already programmed and at your fingertips (in PROC UNIVARIATE using the NORMALTEST option, using&amp;nbsp;the QQPLOT statement or the PROBPLOT statement)&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;But, yes, SAS can produce such inferior information if you want it.&lt;/P&gt;</description>
    <pubDate>Thu, 20 Sep 2018 14:31:01 GMT</pubDate>
    <dc:creator>PaigeMiller</dc:creator>
    <dc:date>2018-09-20T14:31:01Z</dc:date>
    <item>
      <title>Proc Univariate for simple standard problem</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497364#M25714</link>
      <description>&lt;P&gt;Hi all,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I have small sample of severity data of one disease:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;data test;
  infile datalines dlm="," dsd;
  input severity @@;
datalines;                      
0,0,0,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,3,3,3,3,4,4,5,5,5,5,6,7,9,10,11
;
run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;The question is: how to reveal if the sample belongs to population with normal distribution?&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;How to see that 95% of values are within mu +/- 2 sigma,&lt;/P&gt;&lt;P&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 68% of values are within mu +/- 1 sigma,&lt;/P&gt;&lt;P&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; median is nearby mean.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Here it is the code from the adjacent topic but how to see and visualize on diagram median, mean, sigma, 2 sigma, 3 sigma.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;PRE&gt;&lt;CODE class=" language-sas"&gt;proc univariate data=test;
var severity;
histogram severity / href=(2.0 1.0 7.0);
inset P10 median P90 / position=NE;
run;&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 20 Sep 2018 13:46:34 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497364#M25714</guid>
      <dc:creator>DmytroYermak</dc:creator>
      <dc:date>2018-09-20T13:46:34Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Univariate for simple standard problem</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497371#M25715</link>
      <description>&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/58513"&gt;@DmytroYermak&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;
&lt;P&gt;The question is: how to reveal if the sample belongs to population with normal distribution?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;How to see that 95% of values are within mu +/- 2 sigma,&lt;/P&gt;
&lt;P&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; 68% of values are within mu +/- 1 sigma,&lt;/P&gt;
&lt;P&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; median is nearby mean.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;These two are not the same. Testing for normality is not the same as seeing what percent of the values are within mu ± 2 sigma, etc.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;If you really want to test for normality,&amp;nbsp;you might take a look at Q-Q plots in PROC CAPABILITY, and the NORMALTEST option in PROC CAPABILITY.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 20 Sep 2018 14:14:30 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497371#M25715</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2018-09-20T14:14:30Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Univariate for simple standard problem</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497379#M25716</link>
      <description>I am reading "Primer of Biostatistics"(Glanz) and took the first task here. I understand that there are precise normality tests but for the beginners it is 'number of values within sigmas'. Would it be possible with SAS?</description>
      <pubDate>Thu, 20 Sep 2018 14:20:57 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497379#M25716</guid>
      <dc:creator>DmytroYermak</dc:creator>
      <dc:date>2018-09-20T14:20:57Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Univariate for simple standard problem</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497389#M25717</link>
      <description>&lt;BLOCKQUOTE&gt;&lt;HR /&gt;&lt;a href="https://communities.sas.com/t5/user/viewprofilepage/user-id/58513"&gt;@DmytroYermak&lt;/a&gt;&amp;nbsp;wrote:&lt;BR /&gt;&amp;nbsp;for the beginners it is 'number of values within sigmas'&lt;HR /&gt;&lt;/BLOCKQUOTE&gt;
&lt;P&gt;I object to this statement, as I don't see a need to do this computation 'number of values within sigmas' for two reasons:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;It does not really test normality&lt;/LI&gt;
&lt;LI&gt;There are better tests of normality that are already programmed and at your fingertips (in PROC UNIVARIATE using the NORMALTEST option, using&amp;nbsp;the QQPLOT statement or the PROBPLOT statement)&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;But, yes, SAS can produce such inferior information if you want it.&lt;/P&gt;</description>
      <pubDate>Thu, 20 Sep 2018 14:31:01 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497389#M25717</guid>
      <dc:creator>PaigeMiller</dc:creator>
      <dc:date>2018-09-20T14:31:01Z</dc:date>
    </item>
    <item>
      <title>Re: Proc Univariate for simple standard problem</title>
      <link>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497418#M25719</link>
      <description>&lt;P&gt;One way.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;PRE&gt;proc stdize data=test out=temp;
var severity;
run;

proc format library=work;
value sig
-1 &amp;lt;-&amp;lt;1 = '1 sigma'
-2 &amp;lt;- -1= '2 sigma'
1 &amp;lt;-&amp;lt;2  = '2 sigma'
other= 'more than 2 sigma';
run;

proc freq data=temp;
   tables severity;
   format severity sig.;
   label severity='Standardized Severity';
run;&lt;/PRE&gt;
&lt;P&gt;Proc STDIZE default standardization is STD which returns the value of a variables number of std deviations from the mean of the given variable.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Thu, 20 Sep 2018 15:04:47 GMT</pubDate>
      <guid>https://communities.sas.com/t5/Statistical-Procedures/Proc-Univariate-for-simple-standard-problem/m-p/497418#M25719</guid>
      <dc:creator>ballardw</dc:creator>
      <dc:date>2018-09-20T15:04:47Z</dc:date>
    </item>
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