X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=doc%2Fstatistics.texi;h=4966d6afb8ef5ad078b56577be5a827d7af50be4;hb=refs%2Fheads%2Fctables12;hp=adf1f67d95dac39ae5a6f8d04061c0874671867f;hpb=b9f78e2b4d46e219985adc8ab22adf8f67e08b0a;p=pspp

diff --git a/doc/statistics.texi b/doc/statistics.texi
index adf1f67d95..4966d6afb8 100644
--- a/doc/statistics.texi
+++ b/doc/statistics.texi
@@ -923,7 +923,7 @@ where each @i{axis} may be empty or take one of the following forms:
 @i{axis} + @i{axis}
 @i{axis} > @i{axis}
 (@i{axis})
-@i{axis} @t{(}@i{summary} [@i{string}] [@i{format}]@t{)}
+@i{axis} @t{[}@i{summary} [@i{string}] [@i{format}]@t{]}
 @end display
 
 The following subcommands precede the first @code{TABLE} subcommand
@@ -1242,6 +1242,12 @@ for each function is listed in parentheses:
 @item @code{COUNT} (``Count'')
 The sum of weights in a cell.
 
+If @code{CATEGORIES} for one or more of the variables in a table
+include missing values (@pxref{CTABLES Per-Variable Category
+Options}), then some or all of the categories for a cell might be
+missing values.  @code{COUNT} counts data included in a cell
+regardless of whether its categories are missing.
+
 @item @code{@i{area}PCT} or @code{@i{area}PCT.COUNT} (``@i{Area} %'')
 A percentage within the specified @var{area}.
 
@@ -1252,7 +1258,11 @@ A percentage of valid values within the specified @var{area}.
 A percentage of total values within the specified @var{area}.
 @end table
 
-The following summary functions apply only to scalar variables:
+The following summary functions apply only to scalar variables or
+totals and subtotals for categorical variables.  Be cautious about
+interpreting the summary value in the latter case, because it is not
+necessarily meaningful; however, the mean of a Likert scale, etc.@:
+may have a straightforward interpreation.
 
 @table @asis
 @item @code{MAXIMUM} (``Maximum'')
@@ -1292,10 +1302,23 @@ The standard deviation.
 The sum.
 
 @item @code{TOTALN} (``Total N'')
-The sum of total count weights.
+The sum of weights in a cell.
+
+For scale data, @code{COUNT} and @code{TOTALN} are the same.
+
+For categorical data, @code{TOTALN} counts missing values in excluded
+categories, that is, user-missing values not in an explicit category
+list on @code{CATEGORIES} (@pxref{CTABLES Per-Variable Category
+Options}), or user-missing values excluded because
+@code{MISSING=EXCLUDE} is in effect on @code{CATEGORIES}, or
+system-missing values.  @code{COUNT} does not count these.
 
 @item @code{VALIDN} (``Valid N'')
-The sum of valid count weights.
+The sum of valid count weights in included categories.
+
+@code{VALIDN} does not count missing values regardless of whether they
+are in included categories via @code{CATEGORIES}.  @code{VALIDN} does
+not count valid values that are in excluded categories.
 
 @item @code{VARIANCE} (``Variance'')
 The variance.
@@ -1483,7 +1506,7 @@ order:
 
 @table @asis
 @item Explicit categories.
-@anchor{CTABLE Explicit Category List}
+@anchor{CTABLES Explicit Category List}
 To explicitly specify categories to include, list the categories
 within square brackets in the desired sort order.  Use spaces or
 commas to separate values.  Categories not covered by the list are
@@ -1684,9 +1707,46 @@ is optional.
 
 With @code{SMISSING=VARIABLE}, which is the default, missing values
 are excluded on a variable-by-variable basis.  With
-@code{SMISSING=LISTWISE}, when scalar variables are stacked, a missing
-value for any of the scalar variables causes the case to be excluded
-for all of them.
+@code{SMISSING=LISTWISE}, when stacked scalar variables are nested
+together with a categorical variable, a missing value for any of the
+scalar variables causes the case to be excluded for all of them.
+
+As an example, consider the following dataset, in which @samp{x} is a
+categorical variable and @samp{y} and @samp{z} are scale:
+
+@psppoutput{ctables18}
+
+@noindent
+With the default missing-value treatment, @samp{x}'s mean is 20, based
+on the values 10, 20, and 30, and @samp{y}'s mean is 50, based on 40,
+50, and 60:
+
+@example
+CTABLES /TABLE (y + z) > x.
+@end example
+@psppoutput{ctables19}
+
+@noindent
+By adding @code{SMISSING=LISTWISE}, only cases where @samp{y} and
+@samp{z} are both non-missing are considered, so @samp{x}'s mean
+becomes 15, as the average of 10 and 20, and @samp{y}'s mean becomes
+55, the average of 50 and 60:
+
+@example
+CTABLES /SMISSING LISTWISE /TABLE (y + z) > x.
+@end example
+@psppoutput{ctables20}
+
+@noindent
+Even with @code{SMISSING=LISTWISE}, if @samp{y} and @samp{z} are
+separately nested with @samp{x}, instead of using a single @samp{>}
+operator, missing values revert to being considered on a
+variable-by-variable basis:
+
+@example
+CTABLES /SMISSING LISTWISE /TABLE (y > x) + (z > x).
+@end example
+@psppoutput{ctables21}
 
 @node CTABLES Computed Categories
 @subsection Computed Categories
@@ -1699,7 +1759,7 @@ for all of them.
 categories created using arithmetic on categories obtained from the
 data.  The @code{PCOMPUTE} subcommand defines computed categories,
 which can then be used in two places: on @code{CATEGORIES} within an
-explicit category list (@pxref{CTABLE Explicit Category List}), and on
+explicit category list (@pxref{CTABLES Explicit Category List}), and on
 the @code{PPROPERTIES} subcommand to define further properties for a
 given postcompute.
 
@@ -1726,7 +1786,7 @@ postcompute must have the same form.
 @itemx MISSING
 @itemx OTHERNM
 These forms evaluate to the summary statistics for categories matching
-the given syntax, as described in previous sections (@pxref{CTABLE
+the given syntax, as described in previous sections (@pxref{CTABLES
 Explicit Category List}).  If more than one category matches, their
 values are summed.