The PPPLOT statement creates a probability-probability plot (also referred to as a P-P plot or percent plot), which compares the empirical cumulative distribution function (ecdf) of a variable with a specified theoretical cumulative distribution function such as the normal. If the two distributions match, the points on the plot form a linear pattern that passes through the origin and has unit slope. Thus, you can use a P-P plot to determine how well a theoretical distribution models a set of measurements.

You can specify one of the following theoretical distributions with the PPPLOT statement:

• beta

• exponential

• gamma

• lognormal

• normal

• Weibull

You can use options in the PPPLOT statement to do the following:

• specify or estimate parameters for the theoretical distribution

• request graphical enhancements

You can also create a comparative P-P plot by using the PPPLOT statement in conjunction with a CLASS statement.

You have three alternatives for producing P-P plots with the PPPLOT statement:

• Traditional graphics are produced by default.

• ODS Graphics output is produced when you specify the ODS GRAPHICS statement prior to the PROC CAPABILITY statement.

• Legacy line printer plots are produced when you specify the LINEPRINTER option in the PROC CAPABILITY statement.

See Chapter 3, SAS/QC Graphics, for more information about producing these different kinds of graphs.

Note:Probability-probability plots should not be confused with probability plots, which compare a set of ordered measurements with percentiles from a specified distribution. You can create probability plots with the PROBPLOT statement.