are the process variables for which to create P-P plots. If you specify a VAR statement, the variables must also be listed
in the VAR statement. Otherwise, the variables can be any numeric variables in the input data set. If you do not specify a
list of variables, then by default, the procedure creates a P-P plot for each variable listed in the VAR statement or for
each numeric variable in the input data set if you do not specify a VAR statement. For example, each of the following PPPLOT
statements produces two P-P plots, one for length
and one for width
:
proc capability data=measures;
var length width;
ppplot;
run;
proc capability data=measures;
ppplot length width;
run;
specify the theoretical distribution for the plot or add features to the plot. If you specify more than one variable, the
options apply equally to each variable. Specify all options after the slash (/) in the PPPLOT statement. You can specify only
one option naming a distribution, but you can specify any number of other options. The distributions available are the beta,
exponential, gamma, Gumbel, inverse Gaussian, lognormal, normal, generalized Pareto, power function, Rayleigh, and Weibull.
By default, the procedure produces a P-P plot based on the normal distribution.
In the following example, the NORMAL, MU= and SIGMA= options request a P-P plot based on the normal distribution with mean
10 and standard deviation 0.3. The SQUARE option displays the plot in a square frame, and the CTEXT= option specifies the
text color.
proc capability data=measures;
ppplot length width / normal(mu=10 sigma=0.3)
square
ctext=blue;
run;