Note: See p Chart Examples in the SAS/QC Sample Library.
The previous example illustrates how you can create p charts using raw data (counts of nonconforming items). However, in many applications, the data are provided in summarized form as proportions or percentages of nonconforming items. This example illustrates how you can use the PCHART statement with data of this type.
The following data set provides the data from the preceding example in summarized form:
data Cirprop; input Batch pFailed @@; Sampsize=500; datalines; 1 0.010 2 0.012 3 0.022 4 0.012 5 0.008 6 0.018 7 0.034 8 0.020 9 0.024 10 0.018 11 0.016 12 0.014 13 0.014 14 0.030 15 0.016 16 0.036 17 0.024 18 0.032 19 0.008 20 0.014 21 0.034 22 0.024 23 0.016 24 0.014 25 0.030 26 0.012 27 0.016 28 0.024 29 0.014 30 0.018 ;
A partial listing of Cirprop
is shown in Figure 18.63. The subgroups are still indexed by Batch
. The variable pFailed
contains the proportions of nonconforming items, and the variable Sampsize
contains the subgroup sample sizes.
The following statements create a p chart identical to the one in Figure 18.61:
title 'p Chart for the Proportion of Failing Circuits'; proc shewhart data=Cirprop; pchart pFailed*Batch / subgroupn=Sampsize dataunit =proportion; label pfailed = 'Proportion for Fail'; run;
The DATAUNIT=
option specifies that the values of the process (pFailed
) are proportions of nonconforming items. By default, the values of the process are assumed to be counts of nonconforming items (see the previous example).
Alternatively, you can read the data set Cirprop
by specifying it as a HISTORY=
data set in the PROC SHEWHART statement.
A HISTORY= data set used with the PCHART statement must contain the following variables:
subgroup variable
subgroup proportion of nonconforming items variable
subgroup sample size variable
Furthermore, the names of the subgroup proportion and sample size variables must begin with the process name specified in the PCHART statement and end with the special suffix characters P and N, respectively.
To specify Cirprop
as a HISTORY= data set and Fail
as the process, you must rename the variables pFailed
and Sampsize
to FailP
and FailN
, respectively. The following statements temporarily rename pFailed
and Sampsize
for the duration of the procedure step:
options nogstyle; goptions ftext='albany amt'; title 'p Chart for the Proportion of Failing Circuits'; proc shewhart history=Cirprop(rename=(pFailed=FailP Sampsize=FailN )); pchart Fail*Batch / cframe = lib cinfill = bwh coutfill = yellow cconnect = salmon; run; options gstyle;
The NOGSTYLE system option causes ODS styles not to affect traditional graphics. Instead, the PCHART statement options control the appearance of the graph. The GSTYLE system option restores the use of ODS styles for traditional graphics produced subsequently. The resulting p chart is shown in Figure 18.64.
Figure 18.64: p Chart from Subgroup Proportions (Traditional Graphics with NOGSTYLE)
In this example, it is more convenient to use Cirprop
as a DATA= data set than as a HISTORY= data set. In general, it is more convenient to use the HISTORY= option for input data
sets that have been previously created by the SHEWHART procedure as OUTHISTORY=
data sets, as illustrated in the next example. For more information, see HISTORY= Data Set.