15.3 EXAMINE

```EXAMINE
VARIABLES= var1 [var2] … [varN]
[BY factor1 [BY subfactor1]
[ factor2 [BY subfactor2]]
…
[ factor3 [BY subfactor3]]
]
/STATISTICS={DESCRIPTIVES, EXTREME[(n)], ALL, NONE}
/PLOT={BOXPLOT, NPPLOT, HISTOGRAM, SPREADLEVEL[(t)], ALL, NONE}
/CINTERVAL p
/COMPARE={GROUPS,VARIABLES}
/ID=identity_variable
/{TOTAL,NOTOTAL}
/PERCENTILE=[percentiles]={HAVERAGE, WAVERAGE, ROUND, AEMPIRICAL, EMPIRICAL }
/MISSING={LISTWISE, PAIRWISE} [{EXCLUDE, INCLUDE}]
[{NOREPORT,REPORT}]

```

The `EXAMINE` command is used to perform exploratory data analysis. In particular, it is useful for testing how closely a distribution follows a normal distribution, and for finding outliers and extreme values.

The `VARIABLES` subcommand is mandatory. It specifies the dependent variables and optionally variables to use as factors for the analysis. Variables listed before the first `BY` keyword (if any) are the dependent variables. The dependent variables may optionally be followed by a list of factors which tell PSPP how to break down the analysis for each dependent variable.

Following the dependent variables, factors may be specified. The factors (if desired) should be preceded by a single `BY` keyword. The format for each factor is

```factorvar [BY subfactorvar].
```

Each unique combination of the values of factorvar and subfactorvar divide the dataset into cells. Statistics are calculated for each cell and for the entire dataset (unless `NOTOTAL` is given).

The `STATISTICS` subcommand specifies which statistics to show. `DESCRIPTIVES` produces a table showing some parametric and non-parametrics statistics. `EXTREME` produces a table showing the extremities of each cell. A number in parentheses, n determines how many upper and lower extremities to show. The default number is 5.

The subcommands `TOTAL` and `NOTOTAL` are mutually exclusive. If `TOTAL` appears, then statistics for the entire dataset as well as for each cell are produced. If `NOTOTAL` appears, then statistics are produced only for the cells (unless no factor variables have been given). These subcommands have no effect if there have been no factor variables specified.

The `PLOT` subcommand specifies which plots are to be produced if any. Available plots are `HISTOGRAM`, `NPPLOT`, `BOXPLOT` and `SPREADLEVEL`. The first three can be used to visualise how closely each cell conforms to a normal distribution, whilst the spread vs. level plot can be useful to visualise how the variance differs between factors. Boxplots show you the outliers and extreme values. 7

The `SPREADLEVEL` plot displays the interquartile range versus the median. It takes an optional parameter t, which specifies how the data should be transformed prior to plotting. The given value t is a power to which the data are raised. For example, if t is given as 2, then the square of the data is used. Zero, however is a special value. If t is 0 or is omitted, then data are transformed by taking its natural logarithm instead of raising to the power of t.

When one or more plots are requested, `EXAMINE` also performs the Shapiro-Wilk test for each category. There are however a number of provisos:

• All weight values must be integer.
• The cumulative weight value must be in the range [3, 5000]

The `COMPARE` subcommand is only relevant if producing boxplots, and it is only useful there is more than one dependent variable and at least one factor. If `/COMPARE=GROUPS` is specified, then one plot per dependent variable is produced, each of which contain boxplots for all the cells. If `/COMPARE=VARIABLES` is specified, then one plot per cell is produced, each containing one boxplot per dependent variable. If the `/COMPARE` subcommand is omitted, then PSPP behaves as if `/COMPARE=GROUPS` were given.

The `ID` subcommand is relevant only if `/PLOT=BOXPLOT` or `/STATISTICS=EXTREME` has been given. If given, it should provide the name of a variable which is to be used to labels extreme values and outliers. Numeric or string variables are permissible. If the `ID` subcommand is not given, then the case number is used for labelling.

The `CINTERVAL` subcommand specifies the confidence interval to use in calculation of the descriptives command. The default is 95%.

The `PERCENTILES` subcommand specifies which percentiles are to be calculated, and which algorithm to use for calculating them. The default is to calculate the 5, 10, 25, 50, 75, 90, 95 percentiles using the `HAVERAGE` algorithm.

The `TOTAL` and `NOTOTAL` subcommands are mutually exclusive. If `NOTOTAL` is given and factors have been specified in the `VARIABLES` subcommand, then statistics for the unfactored dependent variables are produced in addition to the factored variables. If there are no factors specified then `TOTAL` and `NOTOTAL` have no effect.

The following example generates descriptive statistics and histograms for two variables score1 and score2. Two factors are given, viz: gender and gender BY culture. Therefore, the descriptives and histograms are generated for each distinct value of gender and for each distinct combination of the values of gender and race. Since the `NOTOTAL` keyword is given, statistics and histograms for score1 and score2 covering the whole dataset are not produced.

```EXAMINE score1 score2 BY
gender
gender BY culture
/STATISTICS = DESCRIPTIVES
/PLOT = HISTOGRAM
/NOTOTAL.
```

Here is a second example showing how the `examine` command can be used to find extremities.

```EXAMINE height weight BY
gender
/STATISTICS = EXTREME (3)
/PLOT = BOXPLOT
/COMPARE = GROUPS
/ID = name.
```

In this example, we look at the height and weight of a sample of individuals and how they differ between male and female. A table showing the 3 largest and the 3 smallest values of height and weight for each gender, and for the whole dataset as are shown. In addition, the `/PLOT` subcommand requests boxplots. Because `/COMPARE = GROUPS` was specified, boxplots for male and female are shown in juxtaposed in the same graphic, allowing us to easily see the difference between the genders. Since the variable name was specified on the `ID` subcommand, values of the name variable are used to label the extreme values.

Warning! If you specify many dependent variables or factor variables for which there are many distinct values, then `EXAMINE` will produce a very large quantity of output.

Footnotes

(7)

`HISTOGRAM` uses Sturges’ rule to determine the number of bins, as approximately 1 + \log2(n), where n is the number of samples. Note that `FREQUENCIES` uses a different algorithm to find the bin size.