dividing summary statistic by noobs in proc summary

[csetzkorn]

Using this code:

DATA WORK.TestDataSet;
   INPUT Uid Col1 Col2 Target $;
   DATALINES;
	1 5.1 3.5 13.12345
	2 4.9 3.15 2.1345
;

DATA WORK.TestDataSet;
    SET WORK.TestDataSet;
    MSE = (Target - ((Col1 + Col2) + exp(2.345)))**2;
RUN;

proc summary data = WORK.TestDataSet;
 var MSE;
 output out = WORK.ProcSumOut sum=;
run;

proc print data = WORK.ProcSumOut;
run; 

I would like to divide the 'computed column' by noobs (the number of rows in WORK.TestDataSet). Is this possible? The result should be in WORK.ProcSumOut.

[Jagadishkatam]

I think we cannot divide the computed column in the proc summary. However in a new data step it is possible.

First we need to get the n from proc summary into the WORK.ProcSumOut. Then in the new data step we need to divide the sum with n.

proc summary data = WORK.TestDataSet ;
var MSE;
output out = WORK.ProcSumOut n= sum=;
run;

data WORK.ProcSumOut2;
set WORK.ProcSumOut ;
sum2=sum/n;
run;

Hope this is what you are expecting.

[csetzkorn]

Sorry but your suggestion does not produce the desired output of 151.104. However, the following code, which makes use of _FREQ_. does the job:

DATA WORK.TestDataSet;
   INPUT Uid Col1 Col2 Target $;
   DATALINES;
	1 5.1 3.5 13.12345
	2 4.9 3.15 2.1345
;

DATA WORK.TestDataSet;
    SET WORK.TestDataSet;
    MSE = (Target - ((Col1 + Col2) + exp(2.345)))**2;
RUN;


proc summary data = WORK.TestDataSet ;
	var MSE;
	output out = WORK.ProcSumOut sum=;
run;

proc print data = WORK.ProcSumOut;
run;

data WORK.ProcSumOut2;
	set WORK.ProcSumOut ;
	MSE=MSE/_FREQ_;
run;

proc print data = WORK.ProcSumOut2;
run; 

[Reeza]

proc means data = WORK.TestDataSet ;
var MSE;
output out = WORK.ProcSumOut sum= Mean= / autoname;
run;

[Reeza · Accepted solution]

 Unless you have missing values the average is the sum divided by the number of observations so you can calculate your statistics by specifying the mean option

[Astounding]

If for some reason you want what you are asking for, it's already there.  The output data set automatically contains _FREQ_.  It is the total number of observations (including those that have missing values, so using it in calculations may not give you the mean exactly).

You are specifying that the output data set should contain the SUM.  You can also ask for other statistics, such as MEAN (as Reeza mentioned), N (number of observations with a non-missing value), and NMISS (number of observations with a missing value).