doc: Describe how bin sizes are chosen for histograms.

[pspp] / doc / statistics.texi

diff --git a/doc/statistics.texi b/doc/statistics.texi
index 3a4302873b9f35742b7f32860343c55fd91b49aa..9cc49557ea2ff288b4abd32e57580bc1f68ae115 100644 (file)
--- a/doc/statistics.texi
+++ b/doc/statistics.texi
@@ -8,6 +8,7 @@ far.
 * DESCRIPTIVES::                Descriptive statistics.
 * FREQUENCIES::                 Frequency tables.
 * EXAMINE::                     Testing data for normality.
+* GRAPH::                       Plot data.
 * CORRELATIONS::                Correlation tables.
 * CROSSTABS::                   Crosstabulation tables.
 * FACTOR::                      Factor analysis and Principal Components analysis.
@@ -194,9 +195,13 @@ 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.  Specify @subcmd{NORMAL} to
-superimpose a normal curve on the histogram.  Histograms are not
-created for string variables.
+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.)
+Histograms are not created for string variables.
+
+Specify @subcmd{NORMAL} to superimpose a normal curve on the
+histogram.
 
 @cindex piechart
 The @subcmd{PIECHART} subcommand adds a pie chart for each variable to the data.  Each
@@ -288,6 +293,10 @@ normal distribution, whilst the spread vs.@: level plot can be useful to visuali
 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.)
+
 The @subcmd{SPREADLEVEL} plot displays the interquartile range versus the 
 median.  It takes an optional parameter @var{t}, which specifies how the data
 should be transformed prior to plotting.
@@ -375,6 +384,52 @@ specified for which
 there are many distinct values, then @cmd{EXAMINE} will produce a very
 large quantity of output.
 
+@node GRAPH
+@section GRAPH
+
+@vindex GRAPH
+@cindex Exploratory data analysis
+@cindex normality, testing
+
+@display
+GRAPH
+        /HISTOGRAM = @var{var}
+        /SCATTERPLOT [(BIVARIATE)] = @var{var1} WITH @var{var2} [BY @var{var3}] 
+        [ /MISSING=@{LISTWISE, VARIABLE@} [@{EXCLUDE, INCLUDE@}] ] 
+               [@{NOREPORT,REPORT@}]
+
+@end display
+
+The @cmd{GRAPH} produces graphical plots of data. Only one of the subcommands 
+@subcmd{HISTOGRAM} or @subcmd{SCATTERPLOT} can be specified, i.e. only one plot
+can be produced per call of @cmd{GRAPH}. The @subcmd{MISSING} is optional. 
+
+@cindex scatterplot
+
+The subcommand @subcmd{SCATTERPLOT} produces an xy plot of the data. The different 
+values of the optional third variable @var{var3} will result in different colours and/or
+markers for the plot. The following is an example for producing a scatterplot.
+
+@example
+GRAPH   
+        /SCATTERPLOT = @var{height} WITH @var{weight} BY @var{gender}.
+@end example
+
+This example will produce a scatterplot where height is plotted versus weight. Depending
+on the value of the gender variable, the colour of the datapoint is different. With
+this plot it is possible to analyze gender differences for height vs. weight relation.
+
+@cindex histogram
+
+The subcommand @subcmd{HISTOGRAM} produces a histogram. Only one variable is allowed for
+the histogram plot. For an alternative method to produce histograms @pxref{EXAMINE}. The
+following example produces a histogram plot for variable weigth.
+
+@example
+GRAPH   
+        /HISTOGRAM = @var{weight}.
+@end example
+
 @node CORRELATIONS
 @section CORRELATIONS