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    <title>topic Calculating average age in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301923#M63967</link>
    <description>&lt;P&gt;Hello Everyone,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Below dataset shows the automobile sales for each individual and the duration of time they spent using those vehicles. &lt;SPAN style="line-height: 20px;"&gt;I want to create a table which shows number of individuals who bought 1 vehicle, 2 vehicles, 3 vehicles etc.. Also, I need to know average age of these individuals, %males, %females and average duration these individuals spent using those vehicles. Below is the sample dataset.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;TABLE&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;Customer_ID&lt;/TD&gt;&lt;TD&gt;sales&lt;/TD&gt;&lt;TD&gt;age&lt;/TD&gt;&lt;TD&gt;gender&lt;/TD&gt;&lt;TD&gt;sdate&lt;/TD&gt;&lt;TD&gt;edate&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;12&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;1/1/2001&lt;/TD&gt;&lt;TD&gt;1/12/2001&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;12&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;1/2/2001&lt;/TD&gt;&lt;TD&gt;1/18/2001&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;14&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;1/6/2003&lt;/TD&gt;&lt;TD&gt;1/8/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;22&lt;/TD&gt;&lt;TD&gt;F&lt;/TD&gt;&lt;TD&gt;3/4/2001&lt;/TD&gt;&lt;TD&gt;3/8/2001&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;34&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;2/4/2002&lt;/TD&gt;&lt;TD&gt;2/12/2002&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;34&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;2/10/2002&lt;/TD&gt;&lt;TD&gt;2/24/2002&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;35&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;2/14/2003&lt;/TD&gt;&lt;TD&gt;2/18/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;6&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;74&lt;/TD&gt;&lt;TD&gt;F&lt;/TD&gt;&lt;TD&gt;3/15/2003&lt;/TD&gt;&lt;TD&gt;3/18/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;4&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;40&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;3/15/2003&lt;/TD&gt;&lt;TD&gt;3/18/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;4&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;41&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;3/20/2004&lt;/TD&gt;&lt;TD&gt;3/26/2004&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;5&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;32&lt;/TD&gt;&lt;TD&gt;F&lt;/TD&gt;&lt;TD&gt;3/23/2001&lt;/TD&gt;&lt;TD&gt;3/29/2004&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&lt;BR /&gt;My output should look something like below. First column represent; number of vehicels sold . Second Column represents, how many such individuals bought these vehicles. Example: There was 1 sale for 3 subject IDs (ID-2,6,5), 2 sales for only one ID (ID-4) etc. Now I need find average age of individuals, %males, %females and average duration these individuals used these vehicles.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;TABLE&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;No of vehicles&lt;/TD&gt;&lt;TD&gt;No of Individuals&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;Avg Age (Mean, SD)&lt;/TD&gt;&lt;TD&gt;%males&lt;/TD&gt;&lt;TD&gt;%females&lt;/TD&gt;&lt;TD&gt;Avg duration &amp;nbsp; (Mean, SD)&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The average age of first row in the above table should be: (22+74+32)/3. But, there is an outlier 74 in this age. What is the best way to calculate average age if there is an outlier. Moreover, the third row has two individuals who had three sales. So, will the average age be (12+12+14+34+34+35)/6. How should I calculate. Guide me.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you in advance!&lt;/P&gt;</description>
    <pubDate>Sun, 02 Oct 2016 22:15:22 GMT</pubDate>
    <dc:creator>danwarags</dc:creator>
    <dc:date>2016-10-02T22:15:22Z</dc:date>
    <item>
      <title>Calculating average age</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301923#M63967</link>
      <description>&lt;P&gt;Hello Everyone,&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Below dataset shows the automobile sales for each individual and the duration of time they spent using those vehicles. &lt;SPAN style="line-height: 20px;"&gt;I want to create a table which shows number of individuals who bought 1 vehicle, 2 vehicles, 3 vehicles etc.. Also, I need to know average age of these individuals, %males, %females and average duration these individuals spent using those vehicles. Below is the sample dataset.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;TABLE&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;Customer_ID&lt;/TD&gt;&lt;TD&gt;sales&lt;/TD&gt;&lt;TD&gt;age&lt;/TD&gt;&lt;TD&gt;gender&lt;/TD&gt;&lt;TD&gt;sdate&lt;/TD&gt;&lt;TD&gt;edate&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;12&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;1/1/2001&lt;/TD&gt;&lt;TD&gt;1/12/2001&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;12&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;1/2/2001&lt;/TD&gt;&lt;TD&gt;1/18/2001&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;14&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;1/6/2003&lt;/TD&gt;&lt;TD&gt;1/8/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;22&lt;/TD&gt;&lt;TD&gt;F&lt;/TD&gt;&lt;TD&gt;3/4/2001&lt;/TD&gt;&lt;TD&gt;3/8/2001&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;34&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;2/4/2002&lt;/TD&gt;&lt;TD&gt;2/12/2002&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;34&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;2/10/2002&lt;/TD&gt;&lt;TD&gt;2/24/2002&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;35&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;2/14/2003&lt;/TD&gt;&lt;TD&gt;2/18/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;6&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;74&lt;/TD&gt;&lt;TD&gt;F&lt;/TD&gt;&lt;TD&gt;3/15/2003&lt;/TD&gt;&lt;TD&gt;3/18/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;4&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;40&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;3/15/2003&lt;/TD&gt;&lt;TD&gt;3/18/2003&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;4&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;41&lt;/TD&gt;&lt;TD&gt;M&lt;/TD&gt;&lt;TD&gt;3/20/2004&lt;/TD&gt;&lt;TD&gt;3/26/2004&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;5&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;32&lt;/TD&gt;&lt;TD&gt;F&lt;/TD&gt;&lt;TD&gt;3/23/2001&lt;/TD&gt;&lt;TD&gt;3/29/2004&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&lt;BR /&gt;My output should look something like below. First column represent; number of vehicels sold . Second Column represents, how many such individuals bought these vehicles. Example: There was 1 sale for 3 subject IDs (ID-2,6,5), 2 sales for only one ID (ID-4) etc. Now I need find average age of individuals, %males, %females and average duration these individuals used these vehicles.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;TABLE&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;No of vehicles&lt;/TD&gt;&lt;TD&gt;No of Individuals&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;Avg Age (Mean, SD)&lt;/TD&gt;&lt;TD&gt;%males&lt;/TD&gt;&lt;TD&gt;%females&lt;/TD&gt;&lt;TD&gt;Avg duration &amp;nbsp; (Mean, SD)&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The average age of first row in the above table should be: (22+74+32)/3. But, there is an outlier 74 in this age. What is the best way to calculate average age if there is an outlier. Moreover, the third row has two individuals who had three sales. So, will the average age be (12+12+14+34+34+35)/6. How should I calculate. Guide me.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you in advance!&lt;/P&gt;</description>
      <pubDate>Sun, 02 Oct 2016 22:15:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301923#M63967</guid>
      <dc:creator>danwarags</dc:creator>
      <dc:date>2016-10-02T22:15:22Z</dc:date>
    </item>
    <item>
      <title>Re: Calculating average age</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301925#M63968</link>
      <description>&lt;P&gt;Majority of your requirements are either proc means or proc freq.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;For outliers in your average look at the TRIMMED MEAN in proc means.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&lt;A href="http://support.sas.com/training/tutorial/" target="_blank"&gt;http://support.sas.com/training/tutorial/&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;Look at the Summary Statistics and Descriptive Statistics videos. Right hand side of the page.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sun, 02 Oct 2016 22:46:29 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301925#M63968</guid>
      <dc:creator>Reeza</dc:creator>
      <dc:date>2016-10-02T22:46:29Z</dc:date>
    </item>
    <item>
      <title>Re: Calculating average age</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301938#M63975</link>
      <description>&lt;PRE&gt;
data have;
infile cards expandtabs truncover;
input Customer_ID	sales $	age	gender $ (sdate	edate) (: mmddyy10.);
format sdate edate mmddyy10.;
cards;
1	car	12	M	1/1/2001	1/12/2001
1	bike 	12	M	1/2/2001	1/18/2001
1	truck 	14	M	1/6/2003	1/8/2003
2	car	22	F	3/4/2001	3/8/2001
3	bike 	34	M	2/4/2002	2/12/2002
3	bike 	34	M	2/10/2002	2/24/2002
3	truck 	35	M	2/14/2003	2/18/2003
6	bike 	74	F	3/15/2003	3/18/2003
4	car	40	M	3/15/2003	3/18/2003
4	truck 	41	M	3/20/2004	3/26/2004
5	bike 	32	F	3/23/2001	3/29/2004
;
run;
proc sql;
create table temp as 
 select customer_id,
        count(*) as n,
        avg(age) as age,
        max(gender) as gender,
		avg(edate-sdate) as dur
  from have
   group by customer_id;

create table want as
 select n,
        count(*) as n_individual,
		avg(age) as avg_age,
		std(age) as std_age,
		avg(dur) as avg_dur,
		std(dur) as std_dur,
		sum(gender='F')/count(*) as per_female format=percent7.2,
		sum(gender='M')/count(*) as per_male format=percent7.2
  from temp
   group by n;
quit;



For outliers , you could use proc robustreg or IML function (LTS() LMS() ......) to identify them .
&lt;/PRE&gt;</description>
      <pubDate>Mon, 03 Oct 2016 01:53:41 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301938#M63975</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2016-10-03T01:53:41Z</dc:date>
    </item>
    <item>
      <title>Re: Calculating average age</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301952#M63979</link>
      <description>&lt;P&gt;Thank you so much Ksharp. This was the exact output I needed. But, the only problem is the output dataset shows higher standard deviation for age, which means that there are outliers that needs to be eliminated. I have never used proc robustreg before. I am a physician by profession, so have less stats background. Could you please guide me eliminating outliers in the below dataset.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;TABLE&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;ID&lt;/TD&gt;&lt;TD&gt;sales&lt;/TD&gt;&lt;TD&gt;age&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;12&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;12&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;14&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;22&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;34&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;34&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;35&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;6&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;74&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;4&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;40&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;4&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;41&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;5&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;32&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;7&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;34&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;7&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;35&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;7&lt;/TD&gt;&lt;TD&gt;plane&lt;/TD&gt;&lt;TD&gt;36&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;7&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;37&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;8&lt;/TD&gt;&lt;TD&gt;bike&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;72&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;8&lt;/TD&gt;&lt;TD&gt;car&lt;/TD&gt;&lt;TD&gt;73&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;8&lt;/TD&gt;&lt;TD&gt;plane&lt;/TD&gt;&lt;TD&gt;73&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;8&lt;/TD&gt;&lt;TD&gt;truck&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;74&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;After eliminating outliers my output should look as below:&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;TABLE border="0" cellspacing="0" cellpadding="0"&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;No of vehicles&lt;/TD&gt;&lt;TD&gt;No of IDs&lt;/TD&gt;&lt;TD&gt;Avg Age&lt;/TD&gt;&lt;TD&gt;std Age&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;1&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;3&lt;/TD&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;4&lt;/TD&gt;&lt;TD&gt;2&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;TD&gt;&amp;nbsp;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I really appreciate your help.&amp;nbsp;Thank you in advance.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Mon, 03 Oct 2016 04:21:36 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301952#M63979</guid>
      <dc:creator>danwarags</dc:creator>
      <dc:date>2016-10-03T04:21:36Z</dc:date>
    </item>
    <item>
      <title>Re: Calculating average age</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301972#M63984</link>
      <description>&lt;PRE&gt;
You didn't offer enough data .
Apply the following code, Open dataset OUTLIERS.



data have;
infile cards expandtabs truncover;
input Customer_ID	sales $	age	gender $ (sdate	edate) (: mmddyy10.);
format sdate edate mmddyy10.;
cards;
1	car	12	M	1/1/2001	1/12/2001
1	bike 	12	M	1/2/2001	1/18/2001
1	truck 	14	M	1/6/2003	1/8/2003
2	car	22	F	3/4/2001	3/8/2001
3	bike 	34	M	2/4/2002	2/12/2002
3	bike 	34	M	2/10/2002	2/24/2002
3	truck 	35	M	2/14/2003	2/18/2003
6	bike 	74	F	3/15/2003	3/18/2003
4	car	40	M	3/15/2003	3/18/2003
4	truck 	41	M	3/20/2004	3/26/2004
5	bike 	32	F	3/23/2001	3/29/2004
;
run;
proc robustreg data=have  method=lts;
model age = ;
output out=outliers outlier=outliers;
run;



&lt;/PRE&gt;</description>
      <pubDate>Mon, 03 Oct 2016 07:40:05 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301972#M63984</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2016-10-03T07:40:05Z</dc:date>
    </item>
    <item>
      <title>Re: Calculating average age</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301973#M63985</link>
      <description>&lt;PRE&gt;
Or IML code.


data have;
infile cards expandtabs truncover;
input Customer_ID	sales $	age	gender $ (sdate	edate) (: mmddyy10.);
format sdate edate mmddyy10.;
cards;
1	car	12	M	1/1/2001	1/12/2001
1	bike 	12	M	1/2/2001	1/18/2001
1	truck 	14	M	1/6/2003	1/8/2003
2	car	22	F	3/4/2001	3/8/2001
3	bike 	34	M	2/4/2002	2/12/2002
3	bike 	34	M	2/10/2002	2/24/2002
3	truck 	35	M	2/14/2003	2/18/2003
6	bike 	74	F	3/15/2003	3/18/2003
4	car	40	M	3/15/2003	3/18/2003
4	truck 	41	M	3/20/2004	3/26/2004
5	bike 	32	F	3/23/2001	3/29/2004
;
run;
proc iml;
use have;
read all var{age};
close;

optn = j(9,1,.);
call lms(scLMS, coefLMS, wgtLMS, optn, age);
call lts(scLTS, coefLTS, wgtLTS, optn, age);
LMSOutliers = loc(wgtLMS[1,]=0);
LTSOutliers = loc(wgtLTS[1,]=0);
print LMSOutliers, LTSOutliers;

quit;



OUPTUT: ( the number of obs)

LMSOutliers
1	2	3	8
LTSOutliers
1	2	3	8



&lt;/PRE&gt;</description>
      <pubDate>Mon, 03 Oct 2016 07:49:49 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301973#M63985</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2016-10-03T07:49:49Z</dc:date>
    </item>
    <item>
      <title>Re: Calculating average age</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301983#M63988</link>
      <description>&lt;PRE&gt;

proc robustreg data=have;
model age=/ cutoff=1;
output out=outliers outlier=outlier;
run;
proc print;run;

&lt;/PRE&gt;</description>
      <pubDate>Mon, 03 Oct 2016 08:26:48 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Calculating-average-age/m-p/301983#M63988</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2016-10-03T08:26:48Z</dc:date>
    </item>
  </channel>
</rss>

