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PROC MEANS can be used to compute various univariate descriptive statistics for specified variables including the number of observations, mean, standard deviation, variance, minimum and maximum values, the standard error of the mean, uncorrected sum of squares, corrected sum of squares, the coefficient of variation, and confidence limits for the mean. You can also ask PROC MEANS to perform a t-test on the hypothesis that the population mean IS zero. will automatically compute and print the mean, standard deviation, minimum and maximum values for each of the numeric variables in the most recently created data set. If the linesize of the output window is large enough, PROC MEANS will also print the standard error of the mean, the variance, the sum, and the coefficient of determination. You can specify the data set which PROC MEANS will process by using the DATA= option in the PROC MEANS statement: The VAR statement may be used in conjunction with the PROC MEANS statement to specify the variables for which you want descriptive statistics computed. DATA example1; INPUT name $ 1-10 sex $ 12 age 14-15 height 17-18 weight 20-22 SAS programming statements go here CARDS; Data records go here
PROC MEANS DATA= examplel; VAR age height; RUN', Descriptive statistics will be printed only for the variables specified in the VAR statement. A BY statement can be used with PROC MEANS to obtain separate analyses on observations in groups defined by the variable(s) in the BY statement. When a BY statement appears as part of the MEANS procedure, the procedure expects the data to be sorted in the order of the BY variables. DATA example 1; INPUT name $ 1-10 sex $ 12 age 14-15 height 17-18 weight 20-22 SAS programming statements go here CARDS; Data records go here RUN; PROC SORT DATA = example 1; BY sex; RUN; PROC MEANS DATA= examplel; VAR height weight age; BY sex; RUN', This example will produce a listing of descriptive statistics for females (sex='f') and a separate listing for males (sex='m'). You can ask PROC MEANS to produce only the descriptive statistics you desire. Corresponding to each statistic is a keyword that can be specified in the PROC MEANS statement: number of observations with missing values (in a subgroup)
MEAN STD MIN MAX RANGE SUM VAR USS CSS CV STDERR sample mean sample standard deviation minimum value maximum value range sum vanance uncorrected sum of squares corrected sum of squares coefficient of variation standard error of the mean probability of a greater absolute value for Student's t statistic The confidence intervals have a 95% confidence level (by default). If you desire a different confidence level, use the ALPHA= option on the PROC MEANS statement. For example, to produce 99% confidence limits,
Now for a more complicated example, including a t-test, we might use the following program: DATA example 1; INPUT name $ 1-10 sex $ 12 age 14-15 height 17-18 weight 20-22 SAS programming statements go here CARDS; Data records go here RUN; PROC SORT DATA = example1; BY sex; RUN; PROC MEANS DATA= example1 RUN; N MEAN STD STDERR CLM T PRT ALPHA=0.10; VAR height weight age ;/;51-110 ~ a= () BY sex; With some clever program statements, you can "trick" PROC MEANS into performing tests involving hypotheses other than H o :!!= O. Suppose that you wish to test H o :!! = 60 for the variable height. This can be accomplished by DATA example1; INPUT name $ 1-10 sex $ 12 age 14-15 height 17-18 weight 20-22 /* set up variable for hypothesis test H o :!!= 60 */ htdiff = height - 60; CARDS; t~juo: 11: (P 0 Data records go here PROC MEANS DATA= example1 VAR htdiff; RUN; N MEAN STD STDERR T PRT;
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PROC MEANS can also produce an output data set containing the computed descriptive statistics by using an OUTPUT statement, which has the form DATA examplel; INPUT name $ 1-10 sex $ 12 age 14-15 height 17-18 weight 20-22 SAS program statements go here CARDS; Data records go here PROC MEANS DA TA= example 1 N MEAN STD STDERR; VAR weight; OUTPUT OUT= calcstat N MEAN STD STDERR; RUN; The data set calcstat will contain the specified statistics for the variable weight.
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