FACTOR: Support ANALYSIS subcommand.

[pspp] / doc / statistics.texi

diff --git a/doc/statistics.texi b/doc/statistics.texi
index 7977e3387cc2e0713bbc890d2b1c19000ba7ba77..1e24c173516bcfa62ebb8d8af0ad432e3d1d9a34 100644 (file)
--- a/doc/statistics.texi
+++ b/doc/statistics.texi
@@ -138,6 +138,7 @@ FREQUENCIES
                   [@{FREQ,PERCENT@}] [@{NOMISSING,MISSING@}]
         /BARCHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
                   [@{FREQ,PERCENT@}]
+        /ORDER=@{ANALYSIS,VARIABLE@}
 
 
 (These options are not currently implemented.)
@@ -148,9 +149,8 @@ FREQUENCIES
 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.
@@ -197,9 +197,12 @@ For instance, @subcmd{/NTILES=4} would cause quartiles to be reported.
 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
@@ -228,6 +231,8 @@ 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
 
@@ -306,10 +311,9 @@ 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 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
@@ -705,6 +709,8 @@ FACTOR  VARIABLES=@var{var_list}
 
         [ /METHOD = @{CORRELATION, COVARIANCE@} ]
 
+        [ /ANALYSIS=@var{var_list} ]
+
         [ /EXTRACTION=@{PC, PAF@}] 
 
         [ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, PROMAX[(@var{k})], NOROTATE@}]
@@ -723,7 +729,10 @@ FACTOR  VARIABLES=@var{var_list}
 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.