Introduction
A process capability analysis compares the distribution of output
from an incontrol process to its specification limits
to determine the consistency with which the specifications can be
met.
The CAPABILITY procedure provides the following:
 process capability indices, such as C_{p} and C_{pk}
 descriptive statistics based on moments, including skewness and
kurtosis. Other descriptive information provided includes quantiles or
percentiles (such as the median), frequency tables, and details on
extreme values.
 histograms and comparative histograms.
Optionally, these can be superimposed with
specification limits, 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.
 quantilequantile plots (QQ plots), probability plots, and
probabilityprobability plots (PP plots). These plots facilitate
the comparison of a data distribution with various theoretical
distributions.
Optionally, QQ plots and probability plots
can be superimposed with specification
limits.
 goodnessoffit tests for a variety of distributions
including the normal. The assumption of normality is critical
to the interpretation of capability indices.
 statistical intervals (prediction, tolerance, and
confidence intervals) for a normal population
 the ability to produce plots either on a line printer or
on graphics devices. Plots produced on graphics devices can be
saved, replayed, and annotated.
 the ability to inset summary statistics and capability
indices in plots produced on a graphics device
 the ability to analyze data sets with a frequency variable
 the ability to read specification limits from a data set
 the ability to create output data sets containing
summary statistics, capability indices, histogram intervals,
parameters of fitted curves, and statistical intervals
You can use the PROC CAPABILITY statement, together with the
VAR and SPEC statements, to compute summary statistics and
process capability indices. See "Getting Started"
for introductory examples.
In addition, you can use the statements summarized in the
following table to request plots and specialized analyses:
Statement

Result

CDFPLOT  cumulative distribution function plot 
COMPHISTOGRAM  comparative histogram 
HISTOGRAM  histogram 
INSET  inset table on plot 
INTERVALS  statistical intervals 
OUTPUT  output data set with summary 
 statistics and capability indices 
PPPLOT  probabilityprobability plot 
PROBPLOT  probability plot 
QQPLOT  quantilequantile plot 
You can use the INSET statement with
any of the plot statements to enhance the
plot with an inset table of summary statistics.
The INSET statement is applicable only to plots
produced on graphics devices.