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PPPLOT Statement |

See CAPPP1 in the SAS/QC Sample Library |

The distances between two holes cut into 50 steel
sheets are measured and saved as values of the variable
DISTANCE in the following data set:^{*}

data sheets; input distance @@; label distance='Distance in cm'; datalines; 9.80 10.20 10.27 9.70 9.76 10.11 10.24 10.20 10.24 9.63 9.99 9.78 10.10 10.21 10.00 9.96 9.79 10.08 9.79 10.06 10.10 9.95 9.84 10.11 9.93 10.56 10.47 9.42 10.44 10.16 10.11 10.36 9.94 9.77 9.36 9.89 9.62 10.05 9.72 9.82 9.99 10.16 10.58 10.70 9.54 10.31 10.07 10.33 9.98 10.15 ;The cutting process is in statistical control. As a preliminary step in a capability analysis of the process, it is decided to check whether the distances are normally distributed. The following statements create a P-P plot, shown in Figure 8.1, which is based on the normal distribution with mean and standard deviation :

title 'Normal Probability-Probability Plot for Hole Distance'; proc capability data=sheets noprint; ppplot distance / normal(mu=10 sigma=0.3 color=yellow) square cframe = ligr; run;

The NORMAL option in the PPPLOT statement
requests a P-P plot based on the normal cumulative distribution
function, and the MU= and SIGMA= *normal-options* specify
and . Note that a P-P plot is always based
on a *completely specified* distribution, in other
words, a distribution with specific parameters.
In this example, if you did not specify the MU= and SIGMA=
*normal-options*,
the sample mean and sample standard deviation would be
used for and .

The linearity of the pattern in Figure 8.1
is evidence that the
measurements are normally distributed with mean 10 and
standard deviation 0.3.
The COLOR= *normal-option*
specifies the color for the diagonal reference line, and
the SQUARE option displays the plot in a square format.

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