SCHART Statement: SHEWHART Procedure

Creating Standard Deviation Charts from Subgroup Summary Data

Note: See Standard Deviation Chart (s Chart) Example in the SAS/QC Sample Library.

The previous example illustrates how you can create s charts using raw data (process measurements). However, in many applications, the data are provided as subgroup summary statistics. This example illustrates how you can use the SCHART statement with data of this type.

The following data set (Oilsum) provides the data from the preceding example in summarized form:

data Oilsum;
   input Day KWattsX KWattsS KWattsN;
   informat Day date7. ;
   format Day date5. ;
   label Day   ='Date of Measurement';
   datalines;
 04JUL94 3487.40 220.260 20
 05JUL94 3471.65 210.427 20
 06JUL94 3488.30 147.025 20
 07JUL94 3434.20 157.637 20
 08JUL94 3475.80 258.949 20
 09JUL94 3518.10 211.566 20
 10JUL94 3492.65 193.779 20
 11JUL94 3496.40 212.024 20
 12JUL94 3398.50 199.201 20
 13JUL94 3456.05 173.455 20
 14JUL94 3493.60 187.465 20
 15JUL94 3563.30 205.472 20
 16JUL94 3519.05 173.676 20
 17JUL94 3474.20 200.576 20
 18JUL94 3443.60 222.084 20
 19JUL94 3586.35 185.724 20
 20JUL94 3486.45 223.474 20
 21JUL94 3492.90 145.267 20
 22JUL94 3432.80 190.994 20
 23JUL94 3496.90 208.858 20
;

A partial listing of Oilsum is shown in Figure 17.79. There is exactly one observation for each subgroup (note that the subgroups are still indexed by Day). The variable KWattsX contains the subgroup means, the variable KWattsS contains the subgroup standard deviations, and the variable KWattsN contains the subgroup sample sizes (these are all 20).

Figure 17.79: The Summary Data Set Oilsum

Summary Data Set for Power Outputs

Day KWattsX KWattsS KWattsN
04JUL 3487.40 220.260 20
05JUL 3471.65 210.427 20
06JUL 3488.30 147.025 20
07JUL 3434.20 157.637 20
08JUL 3475.80 258.949 20


You can read this data set by specifying it as a HISTORY= data set in the PROC SHEWHART statement, as follows:

options nogstyle;
goptions ftext=swiss;
title 'Chart for Standard Deviations of Power Output';
proc shewhart history=Oilsum;
   schart KWatts*Day / cframe  = vligb
                       cinfill = ywh
                       cconnect = salmon;
run;
options gstyle;

The NOGSTYLE system option causes ODS styles not to affect traditional graphics. Instead, the SCHART 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 s chart is shown in Figure 17.80.

Figure 17.80: s Chart for Power Output Data (Traditional Graphics with NOGSTYLE)


Note that KWatts is not the name of a SAS variable in the data set Oilsum but is, instead, the common prefix for the names of the SAS variables KWattsS and KWattsN. The suffix characters S and N indicate standard deviation and sample size, respectively. Thus, you can specify two subgroup summary variables in the HISTORY= data set with a single name (KWatts), which is referred to as the process. The name Day, specified after the asterisk, is the name of the subgroup-variable.

In general, a HISTORY= input data set used with the SCHART statement must contain the following variables:

  • subgroup variable

  • subgroup standard deviation variable

  • subgroup sample size variable

Furthermore, the names of the subgroup standard deviation and sample size variables must begin with the process name specified in the SCHART statement and end with the special suffix characters S and N, respectively. If the names do not follow this convention, you can use the RENAME option in the PROC SHEWHART statement to rename the variables for the duration of the SHEWHART procedure step (see Creating Charts for Means and Ranges from Summary Data).

In summary, the interpretation of process depends on the input data set.

  • If raw data are read using the DATA= option (as in the previous example), process is the name of the SAS variable containing the process measurements.

  • If summary data are read using the HISTORY= option (as in this example), process is the common prefix for the names of the variables containing the summary statistics.

For more information, see HISTORY= Data Set.