### 15.1 DESCRIPTIVES ¶

    DESCRIPTIVES
            /VARIABLES=var_list
            /MISSING={VARIABLE,LISTWISE} {INCLUDE,NOINCLUDE}
            /FORMAT={LABELS,NOLABELS} {NOINDEX,INDEX} {LINE,SERIAL}
            /SAVE
            /STATISTICS={ALL,MEAN,SEMEAN,STDDEV,VARIANCE,KURTOSIS,
                         SKEWNESS,RANGE,MINIMUM,MAXIMUM,SUM,DEFAULT,
                         SESKEWNESS,SEKURTOSIS}
            /SORT={NONE,MEAN,SEMEAN,STDDEV,VARIANCE,KURTOSIS,SKEWNESS,
                   RANGE,MINIMUM,MAXIMUM,SUM,SESKEWNESS,SEKURTOSIS,NAME}
                  {A,D}

The `DESCRIPTIVES` procedure reads the active dataset and outputs linear descriptive statistics requested by the user. In addition, it can optionally compute Z-scores.

The `VARIABLES` subcommand, which is required, specifies the list of variables to be analyzed. Keyword `VARIABLES` is optional.

All other subcommands are optional:

The `MISSING` subcommand determines the handling of missing variables. If `INCLUDE` is set, then user-missing values are included in the calculations. If `NOINCLUDE` is set, which is the default, user-missing values are excluded. If `VARIABLE` is set, then missing values are excluded on a variable by variable basis; if `LISTWISE` is set, then the entire case is excluded whenever any value in that case has a system-missing or, if `INCLUDE` is set, user-missing value.

The `FORMAT` subcommand has no effect. It is accepted for backward compatibility.

The `SAVE` subcommand causes `DESCRIPTIVES` to calculate Z scores for all the specified variables. The Z scores are saved to new variables. Variable names are generated by trying first the original variable name with Z prepended and truncated to a maximum of 8 characters, then the names ZSC000 through ZSC999, STDZ00 through STDZ09, ZZZZ00 through ZZZZ09, ZQZQ00 through ZQZQ09, in that sequence. In addition, Z score variable names can be specified explicitly on `VARIABLES` in the variable list by enclosing them in parentheses after each variable. When Z scores are calculated, PSPP ignores `TEMPORARY`, treating temporary transformations as permanent.

The `STATISTICS` subcommand specifies the statistics to be displayed:

``ALL``

  All of the statistics below.

``MEAN``

  Arithmetic mean.

``SEMEAN``

  Standard error of the mean.

``STDDEV``

  Standard deviation.

``VARIANCE``

  Variance.

``KURTOSIS``

  Kurtosis and standard error of the kurtosis.

``SKEWNESS``

  Skewness and standard error of the skewness.

``RANGE``

  Range.

`MINIMUM`

  Minimum value.

`MAXIMUM`

  Maximum value.

`SUM`

  Sum.

`DEFAULT`

  Mean, standard deviation of the mean, minimum, maximum.

`SEKURTOSIS`

  Standard error of the kurtosis.

`SESKEWNESS`

  Standard error of the skewness.

The `SORT` subcommand specifies how the statistics should be sorted. Most of the possible values should be self-explanatory. `NAME` causes the statistics to be sorted by name. By default, the statistics are listed in the order that they are specified on the `VARIABLES` subcommand. The `A` and `D` settings request an ascending or descending sort order, respectively.

#### 15.1.1 Descriptives Example ¶

The `physiology.sav` file contains various physiological data for a sample of persons. Running the `DESCRIPTIVES` command on the variables height and temperature with the default options allows one to see simple linear statistics for these two variables. In Example 15.1, these variables are specfied on the `VARIABLES` subcommand and the `SAVE` option has been used, to request that Z scores be calculated.

After the command has completed, this example runs `DESCRIPTIVES` again, this time on the zheight and ztemperature variables, which are the two normalized (Z-score) variables generated by the first `DESCRIPTIVES` command.

    get file='physiology.sav'.

    descriptives
            /variables = height temperature
            /save.

    descriptives
            /variables = zheight ztemperature.

Example 15.1: Running two `DESCRIPTIVES` commands, one with the `SAVE` subcommand

Screenshot 15.1: The Descriptives dialog box with two variables and Z-Scores option selected

In Result 15.1, we can see that there are 40 valid data for each of the variables and no missing values. The mean average of the height and temperature is 16677.12 and 37.02 respectively. The descriptive statistics for temperature seem reasonable. However there is a very high standard deviation for height and a suspiciously low minimum. This is due to a data entry error in the data (see Identifying incorrect data).

In the second Descriptive Statistics command, one can see that the mean and standard deviation of both Z score variables is 0 and 1 respectively. All Z score statistics should have these properties since they are normalized versions of the original scores.

Mapping of Variables to Z-scores
Source | Target
--- | ---
Height in millimeters | Zheight
Internal body temperature in degrees Celcius | Ztemperature

Descriptive Statistics
| N | Mean | Std Dev | Minimum | Maximum
--- | --- | --- | --- | --- | ---
Height in millimeters | 40 | 1677.12 | 262.87 | 179 | 1903
Internal body temperature in degrees Celcius | 40 | 37.02 | 1.82 | 32.59 | 39.97
Valid N (listwise) | 40 |  |  |  |
Missing N (listwise) | 0 |  |  |  |

Descriptive Statistics
| N | Mean | Std Dev | Minimum | Maximum
--- | --- | --- | --- | --- | ---
Z-score of Height in millimeters | 40 | 1.93E-015 | 1.00 | -5.70 | .86
Z-score of Internal body temperature in degrees Celcius | 40 | 1.37E-015 | 1.00 | -2.44 | 1.62
Valid N (listwise) | 40 |  |  |  |
Missing N (listwise) | 0 |  |  |  |

Result 15.1: Descriptives statistics including two normalized variables (Z-scores)