## PROC CAPABILITY

PROC CAPABILITY is a component of SAS/QC (Quality Control). The features described below are now available in PROC UNIVARIATE (part of base SAS).

PROC CAPABILITY is designed for process capability analysis, but contains many useful features for those of us who can't tell the difference between a capable process and an in-control process, including:

- Histograms and comparative histograms. Optionally, these can be superimposed with fitted
probability density curves for various distributions and kernel density estimates.

- Cumulative distribution function plots (cdf plots). Optionally, these can be
superimposed with specification limits and probability distribution curves for various
distributions.

- Quantile-quantile plots (Q-Q plots), probability plots, and probability-probability
plots (P-P plots). These plots facilitate the comparison of a data distribution with
various theoretical distributions.

- Goodness-of-fit tests for a variety of distributions including the normal.

- Statistical intervals (prediction, tolerance, and confidence intervals) for a normal
population.

- The ability to inset summary statistics and capability indices in plots produced on a
graphics device.

The SAS code described on this page can be downloaded here.

See also the page on SAS/GRAPH.

/* Generate some normally distributed data */ data norm; do i=1 to 500; x=rannor(-5); output; end; run; /* A simple example */ proc capability data=norm graphics normaltest; title 'Histogram using default settings'; var x; histogram x; run; /* A more advanced example */ /* First set some graphics options */ goptions reset=all gunit=pct rotate=landscape htitle=3.0 htext=2.5 noprompt horigin=0.4in vorigin=0.4in vsize=7.0in hsize=10.0in device=win target=winprtg ftext=swiss ; proc capability data=norm graphics normaltest; title 'Histogram using additional options'; var x; histogram x / midpoints=-3.5 to 3.5 by 0.1 normal; inset min median max mean std / format=6.3; run; proc capability data=norm graphics normaltest; title 'Test of normality'; var x; qqplot x / normal (mu=est sigma=est); run;