[@{FREQ[(@var{y_max})],PERCENT[(@var{y_max})]@}] [@{NONORMAL,NORMAL@}]
/PIECHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
[@{FREQ,PERCENT@}] [@{NOMISSING,MISSING@}]
+ /BARCHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
+ [@{FREQ,PERCENT@}]
+ /ORDER=@{ANALYSIS,VARIABLE@}
+
(These options are not currently implemented.)
- /BARCHART=@dots{}
/HBAR=@dots{}
/GROUPED=@dots{}
@end display
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{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 @subcmd{MINIMUM} and @subcmd{MAXIMUM} keywords can be used to limit the
-displayed slices to a given range of values. The @subcmd{MISSING} keyword adds
-slices for missing values.
-
-The @subcmd{FREQ} and @subcmd{PERCENT} options on @subcmd{HISTOGRAM} and @subcmd{PIECHART} are accepted
-but not currently honoured.
+slices.
+The @subcmd{MINIMUM} and @subcmd{MAXIMUM} keywords can be used to limit the
+displayed slices to a given range of values.
+The keyword @subcmd{NOMISSING} causes missing values to be omitted from the
+piechart. This is the default.
+If instead, @subcmd{MISSING} is specified, then a single slice
+will be included representing all system missing and user-missing cases.
+
+@cindex bar chart
+The @subcmd{BARCHART} subcommand produces a bar chart for each variable.
+The @subcmd{MINIMUM} and @subcmd{MAXIMUM} keywords can be used to omit
+categories whose counts which lie outside the specified limits.
+The @subcmd{FREQ} option (default) causes the ordinate to display the frequency
+of each category, whereas the @subcmd{PERCENT} option will display relative
+percentages.
+
+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
ASRESIDUAL,ALL,NONE@}
/STATISTICS=@{CHISQ,PHI,CC,LAMBDA,UC,BTAU,CTAU,RISK,GAMMA,D,
KAPPA,ETA,CORR,ALL,NONE@}
+ /BARCHART
(Integer mode.)
/VARIABLES=@var{var_list} (@var{low},@var{high})@dots{}
@samp{/STATISTICS} without any settings selects CHISQ. If the
@subcmd{STATISTICS} subcommand is not given, no statistics are calculated.
+@cindex bar chart
+The @samp{/BARCHART} subcommand produces a clustered bar chart for the first two
+variables on each table.
+If a table has more than two variables, the counts for the third and subsequent levels
+will be aggregated and the chart will be produces as if there were only two variables.
+
+
@strong{Please note:} Currently the implementation of @cmd{CROSSTABS} has the
-following bugs:
+following limitations:
@itemize @bullet
@item
[ /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.
@display
T-TEST
/MISSING=@{ANALYSIS,LISTWISE@} @{EXCLUDE,INCLUDE@}
- /CRITERIA=CIN(@var{confidence})
+ /CRITERIA=CI(@var{confidence})
(One Sample mode.)
projects / pspp / blobdiff