The QQPLOT statement creates a quantile-quantile plot (Q-Q plot), which compares ordered values of a variable with quantiles 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 Q-Q plot to determine how well a theoretical distribution models a set of measurements.
You can specify one of the following theoretical distributions with the QQPLOT 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 QQPLOT statement to do the following:
specify or estimate parameters for the theoretical distribution
display a reference line corresponding to specific location and scale parameters for the theoretical distribution
request graphical enhancements
You can also create a comparative Q-Q plot by using the QQPLOT statement in conjunction with a CLASS statement.
You have three alternatives for producing Q-Q plots with the QQPLOT 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: Q-Q plots are similar to probability plots, which you can create with the PROBPLOT statement (see PROBPLOT Statement: CAPABILITY Procedure). Q-Q plots are preferable for graphical estimation of distribution parameters and capability indices, whereas probability plots are preferable for graphical estimation of percentiles.