Output Data Sets |

By default, the output data set is a copy of the DATA= data set except that the analyzed variables have been standardized. Analyzed variables are those specified in the VAR statement or, if there is no VAR statement, all numeric variables not listed in any other statement. However, you can use the OPREFIX option to request that both the original and standardized variables be included in the output data set. You can change variable names by specifying prefixes with the OPREFIX=*o-prefix* and SPREFIX=*s-prefix* options, but keep in mind that the two prefixes must be different. See OPREFIX and SPREFIX for more information.

The new data set contains the following variables:

the BY variables, if any

_TYPE_, a character variable

the analyzed variables

Each observation in the new data set contains a type of statistic as indicated by the _TYPE_ variable. The values of the _TYPE_ variable are as follows:

- LOCATION
location measure of each variable

- SCALE
scale measure of each variable

- ADD
constant specified in the ADD= option. This value is the same for each variable.

- MULT
constant specified in the MULT= option. This value is the same for each variable.

- N
total number of nonmissing positive frequencies of each variable

- NORM
norm measure of each variable. This observation is produced only when you specify the NORM option with METHOD=AGK, METHOD=IQR, METHOD=MAD, or METHOD=SPACING or when you specify the SNORM option with METHOD=SPACING.

- NObsRead
number of physical records read

- NObsUsed
number of physical records used in the analysis

- NObsMiss
number of physical records containing missing values

- P
*n* percentiles of each variable, as specified by the PCTLPTS= option. The argument

*n*is any real number such that- SumFreqsRead
sum of the frequency variable (or the sum of NObsUsed ones when there is no frequency variable) for all observations read

- SumFreqsUsed
sum of the frequency variable (or the sum of NObsUsed ones when there is no frequency variable) for all observations used in the analysis

- SumWeightsRead
sum of the weight variable (or the sum of NObsUsed ones when there is no weight variable) for all observations read

- SumWeightsUsed
sum of the weight variable (or the sum of NObsUsed ones when there is no weight variable) for all observations used in the analysis