SAS: Normality Test

A. Reference

B. Data

data BlockDesign;
input block a b y @@;
datalines;
1 1 1 56 1 1 2 41
1 2 1 50 1 2 2 36
1 3 1 39 1 3 2 35
2 1 1 30 2 1 2 25
2 2 1 36 2 2 2 28
2 3 1 33 2 3 2 30
3 1 1 32 3 1 2 24
3 2 1 31 3 2 2 27
3 3 1 15 3 3 2 19
4 1 1 30 4 1 2 25
4 2 1 35 4 2 2 30
4 3 1 17 4 3 2 18
;
run;

C. Normality Check

  • histogram
  • normal
  • plot
  • qqplot
%macro uni (data, var);
Title "Check Nomality and Distribution - &var. in  &data.";
proc univariate data = &data. ;
var &var. ;
histogram / cfill = gray;
run;
proc univariate data = &data. normal plot;
var &var.;
qqplot &var. / normal (mu=est sigma =est);
run;
%mend uni;
%uni(blockdesign, y);

D. Output

The p-value for Shapiro-Wilk test is 0.27, therefore we can not reject the null hypothesis that y is normally distributed.
Q-Q Plot