SAS_ProcMean&Summary

Q)What are the default statistics for means procedure?
A)n-count, mean, standard deviation, minimum, and maximum

Q)How to limit decimal places for variable using PROC MEANS?
A)By using MAXDEC= option

Q)Difference between Proc Means & Proc Summary?
A)Proc SUMMARY and Proc MEANS are essentially the same procedure. Both procedures compute descriptive statistics.
1)The main difference concerns the default type of output they produce.
Proc MEANS by default produces printed output in the LISTING window.
Proc summary by default produces output in a output dataset.

2)No statistics and No VAR statement specified.
When all variables in the data set are character the same output: a simple count of observations, is produced for each procedure.
when some variables in the dataset are numeric, Proc MEANS analyses all numeric variables and produces default statistics for these variables (N, Mean, Standard Deviation, Minimum and Maximum).
Proc Summary produces a simple count of observations

3)If we specify statistics on the PROC SUMMARY statement and the VAR statement is omitted, then PROC SUMMARY stops processing and an error message is written to the SAS log.Proc MEANS produces statistics for numeric variable

Q)what are the differences between a Function & a Proc?
A)we use MEAN function and PROC MEANS to explain the difference.
Functions expects argument value to be supplied across an observation(a row) in a SAS data set and procedure expects one variable value per observation(a column).
For example:
data average ;
set temp ;
avgtemp = mean( of T1 – T24 ) ;
run ;
Here arguments of mean function are taken across an observation.
proc sort ;
by month ;
run ;
proc means ;
by month ;
var avgtemp ;
run ;

 

Proc means is used to calculate average temperature by month (taking one variable value across an observation).

Q)What is the difference between CLASS statement and BY statement in proc means?
A)Unlike CLASS processing, BY processing requires that your data already be sorted or indexed in the order of the BY variables.
BY group results have a layout that is different from the layout of CLASS group results.

Q)Proc Means work for ________ variable and Proc FREQ Work for ______ variable?
A)Numeric, Categorical

Q)How do I add mean values and total count of a categorical variable back to my original data set?
For example: mean values of height for Sex (female and male).
A)
1. Sort the data by Sex.
2. Use Proc Means with BY to create a new data set to hold a mean and count values by Sex.
3. Use a data step with MERGE statements to merge them by Sex.

proc sort data=sashelp.class
out = temp;
by sex ;
proc means data=temp;
var height;
by sex;
output out=new mean=avg_height n =n_height;
run;
data addavg;
merge temp new;
by sex;
drop _type_ _freq_;
run;
proc print data=addavg;
run;

Q) Code a PROC MEANS that shows both summed and averaged output of the data
Raw data

	Name	Sex	Height	Weight
1	Sweety	F	56.5	82
2	Tweety	F	62.5	84.5
3	Preety	F	63.8	86.7
4	Ravi	M	65	112
5	Kappi	M	68.2	114.6
6	Tavi	M	69.7	120
7	Sheena	F	58.4	81
8	Meena	F	61.3	85
9	Raj	M	72	122

A)
proc means data=sashelp.class;
var height weight;
output out=temp
mean= sum=/autoname;
proc print data = temp;
run;

Obs	Sex	_TYPE_	_Freq_	Height_Mean	Weight_Mean	Height_Sum	Height_Sum
1		0	9	64.1555	89.5333	577.4	887.8

 

proc means data=sashelp.class;
class sex;
var height weight;
output out=temp
mean= sum=/autoname;
proc print data = temp;
run;

Obs	Sex	_TYPE_	_Freq_	Height_Mean	Weight_Mean	Height_Sum	Weight_Sum
1		0	9	64.1555	89.5333	577.4	887.8
2	F	1	5	60.5	83.4	302.5	419.2
3	M	1	4	68.725	117.15	274.9	468.6

 

Q) Code the option that will allow MEANS to include missing numeric data to be included in the report.
Raw data

	Name	Sex	Height	Weight
1	Sweety	F	56.5	82
2	Tweety	F	62.5	84.5
3	Preety	F	63.8	86.7
4	Ravi	M	65	112
5	Kappi	M	68.2	114.6
6	Tavi	M	69.7	120
7	Sheena		58.4	81
8	Meena		61.3	85
9	Raj	M	72	122

 

A)
proc means data=sashelp.class missing;
class sex;
var height weight;
output out=temp
mean= sum=/autoname;
proc print data = temp;
run;

Obs	Sex	_TYPE_	_Freq_	Height_Mean	Weight_Mean	Height_Sum	Weight_Sum
1		0	9	64.1555	89.5333	577.4	887.8
2		1	2	59.85	83	119.7	166
3	F	1	3	60.933	84.4	182.8	253.2
4	M	1	4	68.725	117.15	274.9	468.6