The PROBPLOT statement creates a probability plot, which compares ordered values of a variable with percentiles of a specified theoretical distribution such as the normal. If the data distribution matches the theoretical distribution, the points on the plot form a linear pattern. Thus, you can use a probability plot to determine how well a theoretical distribution models a set of measurements.
You can specify one of the following theoretical distributions with the PROBPLOT statement:
beta
exponential
gamma
Gumbel
three-parameter lognormal
normal
generalized Pareto
power function
Rayleigh
two-parameter Weibull
three-parameter Weibull
You can use options in the PROBPLOT statement to do the following:
specify or estimate shape parameters for the theoretical distribution
display a reference line corresponding to specified or estimated location and scale parameters for the theoretical distribution
request graphical enhancements
You can also create a comparative probability plot by using the PROBPLOT statement in conjunction with a CLASS statement.
You have three alternatives for producing probability plots the PROBPLOT statement:
ODS Graphics output is produced if ODS Graphics is enabled, for example by specifying the ODS GRAPHICS ON statement prior to the PROC statement.
Otherwise, traditional graphics are produced by default if SAS/GRAPH^{® }is licensed.
Legacy line printer charts are produced when you specify the LINEPRINTER option in the PROC statement.
See Chapter 3: SAS/QC Graphics, for more information about producing these different kinds of graphs.
Note: Probability plots are similar to Q-Q plots, which you can create with the QQPLOT statement (see QQPLOT Statement: CAPABILITY Procedure). Probability plots are preferable for graphical estimation of percentiles, whereas Q-Q plots are preferable for graphical estimation of distribution parameters and capability indices.