Next: EXAMINE, Previous: DESCRIPTIVES, Up: Statistics [Contents][Index]
FREQUENCIES /VARIABLES=var_list /FORMAT={TABLE,NOTABLE,LIMIT(limit)} {AVALUE,DVALUE,AFREQ,DFREQ} /MISSING={EXCLUDE,INCLUDE} /STATISTICS={DEFAULT,MEAN,SEMEAN,MEDIAN,MODE,STDDEV,VARIANCE, KURTOSIS,SKEWNESS,RANGE,MINIMUM,MAXIMUM,SUM, SESKEWNESS,SEKURTOSIS,ALL,NONE} /NTILES=ntiles /PERCENTILES=percent… /HISTOGRAM=[MINIMUM(x_min)] [MAXIMUM(x_max)] [{FREQ[(y_max)],PERCENT[(y_max)]}] [{NONORMAL,NORMAL}] /PIECHART=[MINIMUM(x_min)] [MAXIMUM(x_max)] [{FREQ,PERCENT}] [{NOMISSING,MISSING}] /BARCHART=[MINIMUM(x_min)] [MAXIMUM(x_max)] [{FREQ,PERCENT}] /ORDER={ANALYSIS,VARIABLE} (These options are not currently implemented.) /HBAR=… /GROUPED=…
The FREQUENCIES
procedure outputs frequency tables for specified
variables.
FREQUENCIES
can also calculate and display descriptive statistics
(including median and mode) and percentiles, and various graphical representations
of the frequency distribution.
The VARIABLES
subcommand is the only required subcommand. Specify the
variables to be analyzed.
The FORMAT
subcommand controls the output format. It has several
possible settings:
TABLE
, the default, causes a frequency table to be output for every
variable specified. NOTABLE
prevents them from being output. LIMIT
with a numeric argument causes them to be output except when there are
more than the specified number of values in the table.
Normally frequency tables are sorted in ascending order by value. This
is AVALUE
. DVALUE
tables are sorted in descending order by value.
AFREQ
and DFREQ
tables are sorted in ascending and descending order,
respectively, by frequency count.
The MISSING
subcommand controls the handling of user-missing values.
When EXCLUDE
, the default, is set, user-missing values are not included
in frequency tables or statistics. When INCLUDE
is set, user-missing
are included. System-missing values are never included in statistics,
but are listed in frequency tables.
The available STATISTICS
are the same as available
in DESCRIPTIVES
(see DESCRIPTIVES), with the addition
of MEDIAN
, the data’s median
value, and MODE, the mode. (If there are multiple modes, the smallest
value is reported.) By default, the mean, standard deviation of the
mean, minimum, and maximum are reported for each variable.
PERCENTILES
causes the specified percentiles to be reported.
The percentiles should be presented at a list of numbers between 0
and 100 inclusive.
The NTILES
subcommand causes the percentiles to be reported at the
boundaries of the data set divided into the specified number of ranges.
For instance, /NTILES=4
would cause quartiles to be reported.
The HISTOGRAM
subcommand causes the output to include a histogram for
each specified numeric variable. The X axis by default ranges from
the minimum to the maximum value observed in the data, but the MINIMUM
and MAXIMUM
keywords can set an explicit range.
6
Histograms are not created for string variables.
Specify NORMAL
to superimpose a normal curve on the
histogram.
The PIECHART
subcommand adds a pie chart for each variable to the data. Each
slice represents one value, with the size of the slice proportional to
the value’s frequency. By default, all non-missing values are given
slices.
The MINIMUM
and MAXIMUM
keywords can be used to limit the
displayed slices to a given range of values.
The keyword NOMISSING
causes missing values to be omitted from the
piechart. This is the default.
If instead, MISSING
is specified, then the pie chart includes
a single slice representing all system missing and user-missing cases.
The BARCHART
subcommand produces a bar chart for each variable.
The MINIMUM
and MAXIMUM
keywords can be used to omit
categories whose counts which lie outside the specified limits.
The FREQ
option (default) causes the ordinate to display the frequency
of each category, whereas the PERCENT
option displays relative
percentages.
The FREQ
and PERCENT
options on HISTOGRAM
and
PIECHART
are accepted but not currently honoured.
The ORDER
subcommand is accepted but ignored.
Example 15.2 runs a frequency analysis on the sex and occupation variables from the personnel.sav file. This is useful to get an general idea of the way in which these nominal variables are distributed.
get file='personnel.sav'. frequencies /variables = sex occupation /statistics = none. |
If you are using the graphic user interface, the dialog box is set up such that by default, several statistics are calculated. Some are not particularly useful for categorical variables, so you may want to disable those.
From Result 15.2 it is evident that there are 33 males, 21 females and 2 persons for whom their sex has not been entered.
One can also see how many of each occupation there are in the data. When dealing with string variables used as nominal values, running a frequency analysis is useful to detect data input entries. Notice that one occupation value has been mistyped as “Scrientist”. This entry should be corrected, or marked as missing before using the data.
|
The number of
bins is chosen according to the Freedman-Diaconis rule:
2 \times IQR(x)n^{-1/3}, where IQR(x) is the interquartile range of x
and n is the number of samples. Note that
EXAMINE
uses a different algorithm to determine bin sizes.
Next: EXAMINE, Previous: DESCRIPTIVES, Up: Statistics [Contents][Index]