[@{FREQ,PERCENT@}] [@{NOMISSING,MISSING@}]
/BARCHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
[@{FREQ,PERCENT@}]
+ /ORDER=@{ANALYSIS,VARIABLE@}
(These options are not currently implemented.)
The @cmd{FREQUENCIES} procedure outputs frequency tables for specified
variables.
@cmd{FREQUENCIES} can also calculate and display descriptive statistics
-(including median and mode) and percentiles,
-@cmd{FREQUENCIES} can also output
-histograms and pie charts.
+(including median and mode) and percentiles, and various graphical representations
+of the frequency distribution.
The @subcmd{VARIABLES} subcommand is the only required subcommand. Specify the
variables to be analyzed.
The @subcmd{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 @subcmd{MINIMUM}
-and @subcmd{MAXIMUM} keywords can set an explicit range. The number of
-bins are 2IQR(x)n^-1/3 according to the Freedman-Diaconis rule. (Note that
-@cmd{EXAMINE} uses a different algorithm to determine bin sizes.)
+and @subcmd{MAXIMUM} keywords can set an explicit range.
+@footnote{The number of
+bins is chosen according to the Freedman-Diaconis rule:
+@math{2 \times IQR(x)n^{-1/3}}, where @math{IQR(x)} is the interquartile range of @math{x}
+and @math{n} is the number of samples. Note that
+@cmd{EXAMINE} uses a different algorithm to determine bin sizes.}
Histograms are not created for string variables.
Specify @subcmd{NORMAL} to superimpose a normal curve on the
The @subcmd{FREQ} and @subcmd{PERCENT} options on @subcmd{HISTOGRAM} and
@subcmd{PIECHART} are accepted but not currently honoured.
+The @subcmd{ORDER} subcommand is accepted but ignored.
+
@node EXAMINE
@section EXAMINE
normal distribution, whilst the spread vs.@: level plot can be useful to visualise
how the variance of differs between factors.
Boxplots will also show you the outliers and extreme values.
-
-@subcmd{HISTOGRAM} uses Sturges' rule to determine the number of
-bins, as approximately 1 + log2(n). (Note that @cmd{FREQUENCIES} uses a
-different algorithm to find the bin size.)
+@footnote{@subcmd{HISTOGRAM} uses Sturges' rule to determine the number of
+bins, as approximately @math{1 + \log2(n)}, where @math{n} is the number of samples.
+Note that @cmd{FREQUENCIES} uses a different algorithm to find the bin size.}
The @subcmd{SPREADLEVEL} plot displays the interquartile range versus the
median. It takes an optional parameter @var{t}, which specifies how the data
[ /METHOD = @{CORRELATION, COVARIANCE@} ]
+ [ /ANALYSIS=@var{var_list} ]
+
[ /EXTRACTION=@{PC, PAF@}]
[ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, PROMAX[(@var{k})], NOROTATE@}]
The @cmd{FACTOR} command performs Factor Analysis or Principal Axis Factoring on a dataset. It may be used to find
common factors in the data or for data reduction purposes.
-The @subcmd{VARIABLES} subcommand is required. It lists the variables which are to partake in the analysis.
+The @subcmd{VARIABLES} subcommand is required. It lists the variables
+which are to partake in the analysis. (The @subcmd{ANALYSIS}
+subcommand may optionally further limit the variables that
+participate; it is not useful and implemented only for compatibility.)
The @subcmd{/EXTRACTION} subcommand is used to specify the way in which factors (components) are extracted from the data.
If @subcmd{PC} is specified, then Principal Components Analysis is used.