Use variable labels in crosstabs.

[pspp] / doc / statistics.texi

diff --git a/doc/statistics.texi b/doc/statistics.texi
index 0b2fdaf5c01b1d41181dfcc8a6d2a11fcb2730f7..b4cbcdd86b23c5ea217eb37a4d60e96d72e8ec89 100644 (file)
--- a/doc/statistics.texi
+++ b/doc/statistics.texi
@@ -361,7 +361,6 @@ CROSSTABS
         /MISSING=@{TABLE,INCLUDE,REPORT@}
         /WRITE=@{NONE,CELLS,ALL@}
         /FORMAT=@{TABLES,NOTABLES@}
-                @{LABELS,NOLABELS,NOVALLABS@}
                 @{PIVOT,NOPIVOT@}
                 @{AVALUE,DVALUE@}
                 @{NOINDEX,INDEX@}
@@ -419,11 +418,6 @@ settings:
 TABLES, the default, causes crosstabulation tables to be output.
 NOTABLES suppresses them.
 
-@item
-LABELS, the default, allows variable labels and value labels to appear
-in the output.  NOLABELS suppresses them.  NOVALLABS displays variable
-labels but suppresses value labels.
-
 @item
 PIVOT, the default, causes each TABLES subcommand to be displayed in a
 pivot table format.  NOPIVOT causes the old-style crosstabulation format
@@ -556,7 +550,7 @@ FACTOR  VARIABLES=var_list
 
         [ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, NOROTATE@}]
 
-        [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [SIG] [ALL] [DEFAULT] ]
+        [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [KMO] [SIG] [ALL] [DEFAULT] ]
 
         [ /PLOT=[EIGEN] ]
 
@@ -601,6 +595,8 @@ The /PRINT subcommand may be used to select which features of the analysis are r
       The covariance matrix is printed.
 @item DET
       The determinant of the correlation or covariance matrix is printed.
+@item KMO
+      The Kaiser-Meyer-Olkin measure of sampling adequacy and the Bartlett test of sphericity is printed.
 @item SIG
       The significance of the elements of correlation matrix is printed.
 @item ALL
@@ -685,9 +681,11 @@ is used.
 * COCHRAN::                 Cochran Q Test
 * FRIEDMAN::                Friedman Test
 * KENDALL::                 Kendall's W Test
+* KOLMOGOROV-SMIRNOV::      Kolmogorov Smirnov Test
 * KRUSKAL-WALLIS::          Kruskal-Wallis Test
 * MANN-WHITNEY::            Mann Whitney U Test
 * MCNEMAR::                 McNemar Test
+* MEDIAN::                  Median Test
 * RUNS::                    Runs Test
 * SIGN::                    The Sign Test
 * WILCOXON::                Wilcoxon Signed Ranks Test
@@ -816,6 +814,45 @@ It has the range [0,1] --- a value of zero indicates no agreement between the sa
 unity indicates complete agreement.
 
 
+@node KOLMOGOROV-SMIRNOV
+@subsection Kolmogorov-Smirnov Test
+@vindex KOLMOGOROV-SMIRNOV
+@vindex K-S
+@cindex Kolmogorov-Smirnov test
+
+@display
+     [ /KOLMOGOROV-SMIRNOV (@{NORMAL [@var{mu}, @var{sigma}], UNIFORM [@var{min}, @var{max}], POISSON [@var{lambda}], EXPONENTIAL [@var{scale}] @}) = varlist ]
+@end display
+
+The one sample Kolmogorov-Smirnov subcommand is used to test whether or not a dataset is
+drawn from a particular distribution.  Four distributions are supported, @i{viz:}
+Normal, Uniform, Poisson and Exponential.
+
+Ideally you should provide the parameters of the distribution against which you wish to test
+the data. For example, with the normal distribution  the mean (@var{mu})and standard deviation (@var{sigma})
+should be given; with the uniform distribution, the minimum (@var{min})and maximum (@var{max}) value should
+be provided.
+However, if the parameters are omitted they will be imputed from the data. Imputing the
+parameters reduces the power of the test so should be avoided if possible.
+
+In the following example, two variables @var{score} and @var{age} are tested to see if
+they follow a normal distribution with a mean of 3.5 and a standard deviation of 2.0.
+@example
+  NPAR TESTS
+        /KOLMOGOROV-SMIRNOV (normal 3.5 2.0) = @var{score} @var{age}.
+@end example
+If the variables need to be tested against different distributions, then a seperate
+subcommand must be used.  For example the following syntax tests @var{score} against
+a normal distribution with mean of 3.5 and standard deviation of 2.0 whilst @var{age}
+is tested against a normal distribution of mean 40 and standard deviation 1.5.
+@example
+  NPAR TESTS
+        /KOLMOGOROV-SMIRNOV (normal 3.5 2.0) = @var{score}
+        /KOLMOGOROV-SMIRNOV (normal 40 1.5) =  @var{age}.
+@end example
+
+The abbreviated subcommand  K-S may be used in place of KOLMOGOROV-SMIRNOV.
+
 @node KRUSKAL-WALLIS
 @subsection Kruskal-Wallis Test
 @vindex KRUSKAL-WALLIS
@@ -889,6 +926,31 @@ The data in each variable must be dichotomous.  If there are more
 than two distinct variables an error will occur and the test will
 not be run.
 
+@node MEDIAN
+@subsection Median Test
+@vindex MEDIAN
+@cindex Median test
+
+@display
+     [ /MEDIAN [(value)] = varlist BY variable (value1, value2) ]
+@end display
+
+The median test is used to test whether independent samples come from 
+populations with a common median.
+The median of the populations against which the samples are to be tested
+may be given in parentheses immediately after the 
+/MEDIAN subcommand.  If it is not given, the median will be imputed from the 
+union of all the samples.
+
+The variables of the samples to be tested should immediately follow the @samp{=} sign. The
+keyword @code{BY} must come next, and then the grouping variable.  Two values
+in parentheses should follow.  If the first value is greater than the second,
+then a 2 sample test is performed using these two values to determine the groups.
+If however, the first variable is less than the second, then a @i{k} sample test is
+conducted and the group values used are all values encountered which lie in the
+range [@var{value1},@var{value2}].
+
+
 @node RUNS
 @subsection Runs Test
 @vindex RUNS