po: Update translations from translationproject.org.

[pspp] / doc / statistics.texi

diff --git a/doc/statistics.texi b/doc/statistics.texi
index 5723323337559ec4076be50b300d9b8152e1a1c2..c46189bd0709394fe2552ee9783915126c9442a3 100644 (file)
--- a/doc/statistics.texi
+++ b/doc/statistics.texi
@@ -1,3 +1,12 @@
+@c PSPP - a program for statistical analysis.
+@c Copyright (C) 2017 Free Software Foundation, Inc.
+@c Permission is granted to copy, distribute and/or modify this document
+@c under the terms of the GNU Free Documentation License, Version 1.3
+@c or any later version published by the Free Software Foundation;
+@c with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
+@c A copy of the license is included in the section entitled "GNU
+@c Free Documentation License".
+@c

 @node Statistics
 @chapter Statistics
 
 @node Statistics
 @chapter Statistics
 


@@ -8,9 +17,11 @@ far.
 * DESCRIPTIVES::                Descriptive statistics.
 * FREQUENCIES::                 Frequency tables.
 * EXAMINE::                     Testing data for normality.
 * 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.
 * CORRELATIONS::                Correlation tables.
 * CROSSTABS::                   Crosstabulation tables.
 * FACTOR::                      Factor analysis and Principal Components analysis.

+* GLM::                         Univariate Linear Models.

 * LOGISTIC REGRESSION::         Bivariate Logistic Regression.
 * MEANS::                       Average values and other statistics.
 * NPAR TESTS::                  Nonparametric tests.
 * LOGISTIC REGRESSION::         Bivariate Logistic Regression.
 * MEANS::                       Average values and other statistics.
 * NPAR TESTS::                  Nonparametric tests.


@@ -73,6 +84,8 @@ names ZSC000 through ZSC999, STDZ00 through STDZ09, ZZZZ00 through
 ZZZZ09, ZQZQ00 through ZQZQ09, in that sequence.  In addition, Z score
 variable names can be specified explicitly on @subcmd{VARIABLES} in the variable
 list by enclosing them in parentheses after each variable.
 ZZZZ09, ZQZQ00 through ZQZQ09, in that sequence.  In addition, Z score
 variable names can be specified explicitly on @subcmd{VARIABLES} in the variable
 list by enclosing them in parentheses after each variable.

+When Z scores are calculated, @pspp{} ignores @cmd{TEMPORARY},
+treating temporary transformations as permanent.

 
 The @subcmd{STATISTICS} subcommand specifies the statistics to be displayed:
 
 
 The @subcmd{STATISTICS} subcommand specifies the statistics to be displayed:
 


@@ -133,9 +146,12 @@ FREQUENCIES
                    [@{FREQ[(@var{y_max})],PERCENT[(@var{y_max})]@}] [@{NONORMAL,NORMAL@}]
         /PIECHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
                   [@{FREQ,PERCENT@}] [@{NOMISSING,MISSING@}]
                    [@{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.)
 
 (These options are not currently implemented.)

-        /BARCHART=@dots{}

         /HBAR=@dots{}
         /GROUPED=@dots{}
 @end display
         /HBAR=@dots{}
         /GROUPED=@dots{}
 @end display


@@ -143,9 +159,8 @@ FREQUENCIES
 The @cmd{FREQUENCIES} procedure outputs frequency tables for specified
 variables.
 @cmd{FREQUENCIES} can also calculate and display descriptive statistics
 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{VARIABLES} subcommand is the only required subcommand.  Specify the
 variables to be analyzed.


@@ -192,27 +207,48 @@ 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}
 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. 
+@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
+histogram.

 
 @cindex piechart
 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
 
 @cindex piechart
 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
 
 @vindex EXAMINE
 @cindex Exploratory data analysis
 
 @node EXAMINE
 @section EXAMINE
 
 @vindex EXAMINE
 @cindex Exploratory data analysis

-@cindex Normality, testing for
+@cindex normality, testing

 
 @display
 EXAMINE
 
 @display
 EXAMINE


@@ -248,7 +284,7 @@ factors which tell @pspp{} how to break down the analysis for each
 dependent variable. 
 
 Following the dependent variables, factors may be specified.
 dependent variable. 
 
 Following the dependent variables, factors may be specified.

-The factors (if desired) should be preceeded by a single @subcmd{BY} keyword.
+The factors (if desired) should be preceded by a single @subcmd{BY} keyword.

 The format for each factor is 
 @display
 @var{factorvar} [BY @var{subfactorvar}].
 The format for each factor is 
 @display
 @var{factorvar} [BY @var{subfactorvar}].


@@ -285,6 +321,9 @@ 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.
 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.

+@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
 
 The @subcmd{SPREADLEVEL} plot displays the interquartile range versus the 
 median.  It takes an optional parameter @var{t}, which specifies how the data


@@ -307,10 +346,10 @@ If the @subcmd{/COMPARE} subcommand is omitted, then @pspp{} behaves as if
  
 The @subcmd{ID} subcommand is relevant only if @subcmd{/PLOT=BOXPLOT} or 
 @subcmd{/STATISTICS=EXTREME} has been given.
  
 The @subcmd{ID} subcommand is relevant only if @subcmd{/PLOT=BOXPLOT} or 
 @subcmd{/STATISTICS=EXTREME} has been given.

-If given, it shoule provide the name of a variable which is to be used
+If given, it should provide the name of a variable which is to be used

 to labels extreme values and outliers.
 Numeric or string variables are permissible.  
 to labels extreme values and outliers.
 Numeric or string variables are permissible.  

-If the @subcmd{ID} subcommand is not given, then the casenumber will be used for
+If the @subcmd{ID} subcommand is not given, then the case number will be used for

 labelling.
 
 The @subcmd{CINTERVAL} subcommand specifies the confidence interval to use in
 labelling.
 
 The @subcmd{CINTERVAL} subcommand specifies the confidence interval to use in


@@ -373,6 +412,121 @@ specified for which
 there are many distinct values, then @cmd{EXAMINE} will produce a very
 large quantity of output.
 
 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 [(NORMAL)]= @var{var}
+        /SCATTERPLOT [(BIVARIATE)] = @var{var1} WITH @var{var2} [BY @var{var3}]
+        /BAR = @{@var{summary-function}(@var{var1}) | @var{count-function}@} BY @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. 
+
+@menu
+* SCATTERPLOT::             Cartesian Plots
+* HISTOGRAM::               Histograms
+* BAR CHART::               Bar Charts
+@end menu
+
+@node SCATTERPLOT
+@subsection Scatterplot
+@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 @var{height} is plotted versus @var{weight}. Depending
+on the value of the @var{gender} variable, the colour of the datapoint is different. With
+this plot it is possible to analyze gender differences for @var{height} vs.@: @var{weight} relation.
+
+@node HISTOGRAM
+@subsection Histogram
+@cindex histogram
+
+The subcommand @subcmd{HISTOGRAM} produces a histogram. Only one variable is allowed for
+the histogram plot.
+The keyword @subcmd{NORMAL} may be specified in parentheses, to indicate that the ideal normal curve
+should be superimposed over the histogram.
+For an alternative method to produce histograms @pxref{EXAMINE}. The
+following example produces a histogram plot for the variable @var{weight}.
+
+@example
+GRAPH   
+        /HISTOGRAM = @var{weight}.
+@end example
+
+@node BAR CHART
+@subsection Bar Chart
+@cindex bar chart
+
+The subcommand @subcmd{BAR} produces a bar chart.
+This subcommand requires that a @var{count-function} be specified (with no arguments) or a @var{summary-function} with a variable @var{var1} in parentheses.
+Following the summary or count function, the keyword @subcmd{BY} should be specified and then a catagorical variable, @var{var2}.
+The values of the variable @var{var2} determine the labels of the bars to be plotted.
+Optionally a second categorical variable @var{var3} may be specified in which case a clustered (grouped) bar chart is produced.
+
+Valid count functions are
+@table @subcmd
+@item COUNT
+The weighted counts of the cases in each category.
+@item PCT
+The weighted counts of the cases in each category expressed as a percentage of the total weights of the cases.
+@item CUFREQ
+The cumulative weighted counts of the cases in each category.
+@item CUPCT
+The cumulative weighted counts of the cases in each category expressed as a percentage of the total weights of the cases.
+@end table
+
+The summary function is applied to @var{var1} across all cases in each category.
+The recognised summary functions are:
+@table @subcmd
+@item SUM
+The sum.
+@item MEAN
+The arithmetic mean.
+@item MAXIMUM
+The maximum value.
+@item MINIMUM
+The minimum value.
+@end table
+
+The following examples assume a dataset which is the results of a survey.
+Each respondent has indicated annual income, their sex and city of residence.
+One could create a bar chart showing how the mean income varies between of residents of different cities, thus:
+@example
+GRAPH  /BAR  = MEAN(@var{income}) BY @var{city}.
+@end example
+
+This can be extended to also indicate how income in each city differs between the sexes.
+@example
+GRAPH  /BAR  = MEAN(@var{income}) BY @var{city} BY @var{sex}.
+@end example
+
+One might also want to see how many respondents there are from each city.  This can be achieved as follows:
+@example
+GRAPH  /BAR  = COUNT BY @var{city}.
+@end example
+
+Bar charts can also be produced using the @ref{FREQUENCIES} and @ref{CROSSTABS} commands.
+

 @node CORRELATIONS
 @section CORRELATIONS
 
 @node CORRELATIONS
 @section CORRELATIONS
 


@@ -452,8 +606,11 @@ CROSSTABS
                 @{BOX,NOBOX@}
         /CELLS=@{COUNT,ROW,COLUMN,TOTAL,EXPECTED,RESIDUAL,SRESIDUAL,
                 ASRESIDUAL,ALL,NONE@}
                 @{BOX,NOBOX@}
         /CELLS=@{COUNT,ROW,COLUMN,TOTAL,EXPECTED,RESIDUAL,SRESIDUAL,
                 ASRESIDUAL,ALL,NONE@}

+        /COUNT=@{ASIS,CASE,CELL@}
+               @{ROUND,TRUNCATE@}

         /STATISTICS=@{CHISQ,PHI,CC,LAMBDA,UC,BTAU,CTAU,RISK,GAMMA,D,
                      KAPPA,ETA,CORR,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{}
         
 (Integer mode.)
         /VARIABLES=@var{var_list} (@var{low},@var{high})@dots{}


@@ -498,7 +655,7 @@ The @subcmd{FORMAT} subcommand controls the characteristics of the
 crosstabulation tables to be displayed.  It has a number of possible
 settings:
 
 crosstabulation tables to be displayed.  It has a number of possible
 settings:
 

-@itemize @asis
+@itemize @w{}

 @item
 @subcmd{TABLES}, the default, causes crosstabulation tables to be output.
 @subcmd{NOTABLES} suppresses them.
 @item
 @subcmd{TABLES}, the default, causes crosstabulation tables to be output.
 @subcmd{NOTABLES} suppresses them.


@@ -550,6 +707,15 @@ Suppress cells entirely.
 If @subcmd{CELLS} is not specified at all then only @subcmd{COUNT}
 will be selected.
 
 If @subcmd{CELLS} is not specified at all then only @subcmd{COUNT}
 will be selected.
 

+By default, crosstabulation and statistics use raw case weights,
+without rounding.  Use the @subcmd{/COUNT} subcommand to perform
+rounding: CASE rounds the weights of individual weights as cases are
+read, CELL rounds the weights of cells within each crosstabulation
+table after it has been constructed, and ASIS explicitly specifies the
+default non-rounding behavior.  When rounding is requested, ROUND, the
+default, rounds to the nearest integer and TRUNCATE rounds toward
+zero.
+

 The @subcmd{STATISTICS} subcommand selects statistics for computation:
 
 @table @asis
 The @subcmd{STATISTICS} subcommand selects statistics for computation:
 
 @table @asis


@@ -596,24 +762,24 @@ some statistics are calculated only in integer mode.
 @samp{/STATISTICS} without any settings selects CHISQ.  If the
 @subcmd{STATISTICS} subcommand is not given, no statistics are calculated.
 
 @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
 @strong{Please note:} Currently the implementation of @cmd{CROSSTABS} has the

-followings bugs:
+following limitations:

 
 @itemize @bullet
 @item
 
 @itemize @bullet
 @item

-Pearson's R (but not Spearman) is off a little.
-@item
-T values for Spearman's R and Pearson's R are wrong.
-@item
-Significance of symmetric and directional measures is not calculated.
-@item
-Asymmetric ASEs and T values for lambda are wrong.
+Significance of some symmetric and directional measures is not calculated.

 @item
 @item

-ASE of Goodman and Kruskal's tau is not calculated.
+Asymptotic standard error is not calculated for
+Goodman and Kruskal's tau or symmetric Somers' d.

 @item
 @item

-ASE of symmetric somers' d is wrong.
-@item
-Approximate T of uncertainty coefficient is wrong.
+Approximate T is not calculated for symmetric uncertainty coefficient.

 @end itemize
 
 Fixes for any of these deficiencies would be welcomed.
 @end itemize
 
 Fixes for any of these deficiencies would be welcomed.


@@ -628,15 +794,20 @@ Fixes for any of these deficiencies would be welcomed.
 @cindex data reduction
 
 @display
 @cindex data reduction
 
 @display

-FACTOR  VARIABLES=@var{var_list}
+FACTOR  @{
+         VARIABLES=@var{var_list},
+         MATRIX IN (@{CORR,COV@}=@{*,@var{file_spec}@})
+        @}

 
         [ /METHOD = @{CORRELATION, COVARIANCE@} ]
 
 
         [ /METHOD = @{CORRELATION, COVARIANCE@} ]
 

+        [ /ANALYSIS=@var{var_list} ]
+

         [ /EXTRACTION=@{PC, PAF@}] 
 
         [ /EXTRACTION=@{PC, PAF@}] 
 

-        [ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, NOROTATE@}]
+        [ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, PROMAX[(@var{k})], NOROTATE@}]

 
 

-        [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [KMO] [SIG] [ALL] [DEFAULT] ]
+        [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [KMO] [AIC] [SIG] [ALL] [DEFAULT] ]

 
         [ /PLOT=[EIGEN] ]
 
 
         [ /PLOT=[EIGEN] ]
 


@@ -650,7 +821,21 @@ 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 @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 (unless the @subcmd{MATRIX IN}
+subcommand is used).
+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 useful primarily in conjunction with @subcmd{MATRIX IN}.)
+
+If @subcmd{MATRIX IN} instead of @subcmd{VARIABLES} is specified, then the analysis
+is performed on a pre-prepared correlation or covariance matrix file instead of on
+individual data cases.  Typically the matrix file will have been generated by
+@cmd{MATRIX DATA} (@pxref{MATRIX DATA}) or provided by a third party.
+If specified, @subcmd{MATRIX IN} must be followed by @samp{COV} or @samp{CORR},
+then by @samp{=} and @var{file_spec} all in parentheses.
+@var{file_spec} may either be an asterisk, which indicates the currently loaded
+dataset, or it may be a filename to be loaded. @xref{MATRIX DATA}, for the expected
+format of the file.

 
 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.  
 
 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.  


@@ -658,9 +843,13 @@ If @subcmd{PAF} is specified, then Principal Axis Factoring is
 used. By default Principal Components Analysis will be used.
 
 The @subcmd{/ROTATION} subcommand is used to specify the method by which the extracted solution will be rotated.
 used. By default Principal Components Analysis will be used.
 
 The @subcmd{/ROTATION} subcommand is used to specify the method by which the extracted solution will be rotated.

-Three methods are available: @subcmd{VARIMAX} (which is the default), @subcmd{EQUAMAX}, and @subcmd{QUARTIMAX}.
-If don't want any rotation to be performed, the word @subcmd{NOROTATE} will prevent the command from performing any
-rotation on the data. Oblique rotations are not supported.
+Three orthogonal rotation methods are available: 
+@subcmd{VARIMAX} (which is the default), @subcmd{EQUAMAX}, and @subcmd{QUARTIMAX}.
+There is one oblique rotation method, @i{viz}: @subcmd{PROMAX}.
+Optionally you may enter the power of the promax rotation @var{k}, which must be enclosed in parentheses.
+The default value of @var{k} is 5.
+If you don't want any rotation to be performed, the word @subcmd{NOROTATE} will prevent the command from performing any
+rotation on the data. 

 
 The @subcmd{/METHOD} subcommand should be used to determine whether the covariance matrix or the correlation matrix of the data is
 to be analysed.  By default, the correlation matrix is analysed.
 
 The @subcmd{/METHOD} subcommand should be used to determine whether the covariance matrix or the correlation matrix of the data is
 to be analysed.  By default, the correlation matrix is analysed.


@@ -682,6 +871,8 @@ The @subcmd{/PRINT} subcommand may be used to select which features of the analy
       The covariance matrix is printed.
 @item @subcmd{DET}
       The determinant of the correlation or covariance matrix is printed.
       The covariance matrix is printed.
 @item @subcmd{DET}
       The determinant of the correlation or covariance matrix is printed.

+@item @subcmd{AIC}
+      The anti-image covariance and anti-image correlation matrices are printed.

 @item @subcmd{KMO}
       The Kaiser-Meyer-Olkin measure of sampling adequacy and the Bartlett test of sphericity is printed.
 @item @subcmd{SIG}
 @item @subcmd{KMO}
       The Kaiser-Meyer-Olkin measure of sampling adequacy and the Bartlett test of sphericity is printed.
 @item @subcmd{SIG}


@@ -703,13 +894,23 @@ performed, and all coefficients will be printed.
 The @subcmd{/CRITERIA} subcommand is used to specify how the number of extracted factors (components) are chosen.
 If @subcmd{FACTORS(@var{n})} is
 specified, where @var{n} is an integer, then @var{n} factors will be extracted.  Otherwise, the @subcmd{MINEIGEN} setting will
 The @subcmd{/CRITERIA} subcommand is used to specify how the number of extracted factors (components) are chosen.
 If @subcmd{FACTORS(@var{n})} is
 specified, where @var{n} is an integer, then @var{n} factors will be extracted.  Otherwise, the @subcmd{MINEIGEN} setting will

-be used.  @subcmd{MINEIGEN(@var{l})} requests that all factors whose eigenvalues are greater than or equal to @var{l} are extracted.
-The default value of @var{l} is 1.    The @subcmd{ECONVERGE} and @subcmd{ITERATE} settings have effect only when iterative algorithms for factor
-extraction (such as Principal Axis Factoring) are used.   @subcmd{ECONVERGE(@var{delta})} specifies that
+be used.  
+@subcmd{MINEIGEN(@var{l})} requests that all factors whose eigenvalues are greater than or equal to @var{l} are extracted.
+The default value of @var{l} is 1.    
+The @subcmd{ECONVERGE} setting has effect only when iterative algorithms for factor
+extraction (such as Principal Axis Factoring) are used.   
+@subcmd{ECONVERGE(@var{delta})} specifies that

 iteration should cease when
 the maximum absolute value of the communality estimate between one iteration and the previous is less than @var{delta}. The
 default value of @var{delta} is 0.001.
 iteration should cease when
 the maximum absolute value of the communality estimate between one iteration and the previous is less than @var{delta}. The
 default value of @var{delta} is 0.001.

-The @subcmd{ITERATE(@var{m})} setting sets the maximum number of iterations to @var{m}.  The default value of @var{m} is 25.
+The @subcmd{ITERATE(@var{m})} may appear any number of times and is used for two different purposes.  
+It is used to set the maximum number of iterations (@var{m}) for convergence and also to set the maximum number of iterations
+for rotation.
+Whether it affects convergence or rotation depends upon which subcommand follows the @subcmd{ITERATE} subcommand.
+If @subcmd{EXTRACTION} follows, it affects convergence.  
+If @subcmd{ROTATION} follows, it affects rotation.  
+If neither @subcmd{ROTATION} nor @subcmd{EXTRACTION} follow a @subcmd{ITERATE} subcommand it will be ignored.
+The default value of @var{m} is 25.

 
 The @cmd{MISSING} subcommand determines the handling of missing variables.  
 If @subcmd{INCLUDE} is set, then user-missing values are included in the
 
 The @cmd{MISSING} subcommand determines the handling of missing variables.  
 If @subcmd{INCLUDE} is set, then user-missing values are included in the


@@ -724,6 +925,65 @@ If @subcmd{PAIRWISE} is set, then a case is considered missing only if either of
 values  for the particular coefficient are missing.
 The default is @subcmd{LISTWISE}.
 
 values  for the particular coefficient are missing.
 The default is @subcmd{LISTWISE}.
 

+@node GLM
+@section GLM
+
+@vindex GLM
+@cindex univariate analysis of variance
+@cindex fixed effects
+@cindex factorial anova
+@cindex analysis of variance
+@cindex ANOVA
+
+
+@display
+GLM @var{dependent_vars} BY @var{fixed_factors}
+     [/METHOD = SSTYPE(@var{type})]
+     [/DESIGN = @var{interaction_0} [@var{interaction_1} [... @var{interaction_n}]]]
+     [/INTERCEPT = @{INCLUDE|EXCLUDE@}]
+     [/MISSING = @{INCLUDE|EXCLUDE@}]
+@end display
+
+The @cmd{GLM} procedure can be used for fixed effects factorial Anova.
+
+The @var{dependent_vars} are the variables to be analysed.
+You may analyse several variables in the same command in which case they should all
+appear before the @code{BY} keyword.
+
+The @var{fixed_factors} list must be one or more categorical variables.  Normally it
+will not make sense to enter a scalar variable in the @var{fixed_factors} and doing
+so may cause @pspp{} to do a lot of unnecessary processing.
+
+The @subcmd{METHOD} subcommand is used to change the method for producing the sums of
+squares.  Available values of @var{type} are 1, 2 and 3.  The default is type 3.
+
+You may specify a custom design using the @subcmd{DESIGN} subcommand.
+The design comprises a list of interactions where each interaction is a 
+list of variables separated by a @samp{*}.  For example the command
+@display
+GLM subject BY sex age_group race
+    /DESIGN = age_group sex group age_group*sex age_group*race
+@end display
+@noindent specifies the model @math{subject = age_group + sex + race + age_group*sex + age_group*race}.
+If no @subcmd{DESIGN} subcommand is specified, then the default is all possible combinations
+of the fixed factors.  That is to say
+@display
+GLM subject BY sex age_group race
+@end display
+implies the model
+@math{subject = age_group + sex + race + age_group*sex + age_group*race + sex*race + age_group*sex*race}.
+
+
+The @subcmd{MISSING} subcommand determines the handling of missing
+variables.  
+If @subcmd{INCLUDE} is set then, for the purposes of GLM analysis,
+only system-missing values are considered
+to be missing; user-missing values are not regarded as missing.
+If @subcmd{EXCLUDE} is set, which is the default, then user-missing
+values are considered to be missing as well as system-missing values. 
+A case for which any dependent variable or any factor
+variable has a missing value is excluded from the analysis.
+

 @node LOGISTIC REGRESSION
 @section LOGISTIC REGRESSION
 
 @node LOGISTIC REGRESSION
 @section LOGISTIC REGRESSION
 


@@ -741,7 +1001,8 @@ LOGISTIC REGRESSION [VARIABLES =] @var{dependent_var} WITH @var{predictors}
      [/PRINT = [SUMMARY] [DEFAULT] [CI(@var{confidence})] [ALL]]
 
      [/CRITERIA = [BCON(@var{min_delta})] [ITERATE(@var{max_interations})]
      [/PRINT = [SUMMARY] [DEFAULT] [CI(@var{confidence})] [ALL]]
 
      [/CRITERIA = [BCON(@var{min_delta})] [ITERATE(@var{max_interations})]

-                  [LCON(@var{min_likelihood_delta})] [EPS(@var{min_epsilon})]]
+                  [LCON(@var{min_likelihood_delta})] [EPS(@var{min_epsilon})]
+                  [CUT(@var{cut_point})]]

 
      [/MISSING = @{INCLUDE|EXCLUDE@}]
 @end display
 
      [/MISSING = @{INCLUDE|EXCLUDE@}]
 @end display


@@ -773,10 +1034,14 @@ If you want a model without the constant term @math{b_0}, use the keyword @subcm
 @subcmd{/NOCONST} is a synonym for @subcmd{/ORIGIN}.
 
 An iterative Newton-Raphson procedure is used to fit the model.
 @subcmd{/NOCONST} is a synonym for @subcmd{/ORIGIN}.
 
 An iterative Newton-Raphson procedure is used to fit the model.

-The @subcmd{/CRITERIA} subcommand is used to specify the stopping criteria of the procedure.
+The @subcmd{/CRITERIA} subcommand is used to specify the stopping criteria of the procedure,
+and other parameters.
+The value of @var{cut_point} is used in the classification table.  It is the 
+threshold above which predicted values are considered to be 1.  Values
+of @var{cut_point} must lie in the range [0,1].

 During iterations, if any one of the stopping criteria are satisfied, the procedure is
 considered complete.
 During iterations, if any one of the stopping criteria are satisfied, the procedure is
 considered complete.

-The criteria are:
+The stopping criteria are:

 @itemize
 @item The number of iterations exceeds @var{max_iterations}.  
       The default value of @var{max_iterations} is 20.
 @itemize
 @item The number of iterations exceeds @var{max_iterations}.  
       The default value of @var{max_iterations} is 20.


@@ -790,6 +1055,7 @@ In other words, the probabilities are close to zero or one.
 The default value of @var{min_epsilon} is 0.00000001.
 @end itemize
 
 The default value of @var{min_epsilon} is 0.00000001.
 @end itemize
 

+

 The @subcmd{PRINT} subcommand controls the display of optional statistics.
 Currently there is one such option, @subcmd{CI}, which indicates that the 
 confidence interval of the odds ratio should be displayed as well as its value.
 The @subcmd{PRINT} subcommand controls the display of optional statistics.
 Currently there is one such option, @subcmd{CI}, which indicates that the 
 confidence interval of the odds ratio should be displayed as well as its value.


@@ -1067,7 +1333,7 @@ outside the  specified range are excluded from the analysis.
 The @subcmd{/EXPECTED} subcommand specifies the expected values of each
 category.  
 There must be exactly one non-zero expected value, for each observed
 The @subcmd{/EXPECTED} subcommand specifies the expected values of each
 category.  
 There must be exactly one non-zero expected value, for each observed

-category, or the @subcmd{EQUAL} keywork must be specified.
+category, or the @subcmd{EQUAL} keyword must be specified.

 You may use the notation @subcmd{@var{n}*@var{f}} to specify @var{n}
 consecutive expected categories all taking a frequency of @var{f}.
 The frequencies given are proportions, not absolute frequencies.  The
 You may use the notation @subcmd{@var{n}*@var{f}} to specify @var{n}
 consecutive expected categories all taking a frequency of @var{f}.
 The frequencies given are proportions, not absolute frequencies.  The


@@ -1318,7 +1584,7 @@ of variable preceding @code{WITH} against variable following
 The @subcmd{/WILCOXON} subcommand tests for differences between medians of the 
 variables listed.
 The test does not make any assumptions about the variances of the samples.
 The @subcmd{/WILCOXON} subcommand tests for differences between medians of the 
 variables listed.
 The test does not make any assumptions about the variances of the samples.

-It does however assume that the distribution is symetrical.
+It does however assume that the distribution is symmetrical.

 
 If the @subcmd{WITH} keyword is omitted, then tests for all
 combinations of the listed variables are performed.
 
 If the @subcmd{WITH} keyword is omitted, then tests for all
 combinations of the listed variables are performed.


@@ -1340,7 +1606,7 @@ of variable preceding @subcmd{WITH} against variable following
 @display
 T-TEST
         /MISSING=@{ANALYSIS,LISTWISE@} @{EXCLUDE,INCLUDE@}
 @display
 T-TEST
         /MISSING=@{ANALYSIS,LISTWISE@} @{EXCLUDE,INCLUDE@}

-        /CRITERIA=CIN(@var{confidence})
+        /CRITERIA=CI(@var{confidence})

 
 
 (One Sample mode.)
 
 
 (One Sample mode.)


@@ -1482,7 +1748,7 @@ The list of variables must be followed by the @subcmd{BY} keyword and
 the name of the independent (or factor) variable.
 
 You can use the @subcmd{STATISTICS} subcommand to tell @pspp{} to display
 the name of the independent (or factor) variable.
 
 You can use the @subcmd{STATISTICS} subcommand to tell @pspp{} to display

-ancilliary information.  The options accepted are:
+ancillary information.  The options accepted are:

 @itemize
 @item DESCRIPTIVES
 Displays descriptive statistics about the groups factored by the independent
 @itemize
 @item DESCRIPTIVES
 Displays descriptive statistics about the groups factored by the independent


@@ -1545,8 +1811,9 @@ The default is 0.05.
 
 @display
 QUICK CLUSTER @var{var_list}
 
 @display
 QUICK CLUSTER @var{var_list}

-      [/CRITERIA=CLUSTERS(@var{k}) [MXITER(@var{max_iter})]]
+      [/CRITERIA=CLUSTERS(@var{k}) [MXITER(@var{max_iter})] CONVERGE(@var{epsilon}) [NOINITIAL]]

       [/MISSING=@{EXCLUDE,INCLUDE@} @{LISTWISE, PAIRWISE@}]
       [/MISSING=@{EXCLUDE,INCLUDE@} @{LISTWISE, PAIRWISE@}]

+      [/PRINT=@{INITIAL@} @{CLUSTER@}]

 @end display
 
 The @cmd{QUICK CLUSTER} command performs k-means clustering on the
 @end display
 
 The @cmd{QUICK CLUSTER} command performs k-means clustering on the


@@ -1556,11 +1823,29 @@ of similar values and you already know the number of clusters.
 The minimum specification is @samp{QUICK CLUSTER} followed by the names
 of the variables which contain the cluster data.  Normally you will also
 want to specify @subcmd{/CRITERIA=CLUSTERS(@var{k})} where @var{k} is the
 The minimum specification is @samp{QUICK CLUSTER} followed by the names
 of the variables which contain the cluster data.  Normally you will also
 want to specify @subcmd{/CRITERIA=CLUSTERS(@var{k})} where @var{k} is the

-number of clusters.  If this is not given, then @var{k} defaults to 2.
+number of clusters.  If this is not specified, then @var{k} defaults to 2.
+
+If you use @subcmd{/CRITERIA=NOINITIAL} then a naive algorithm to select
+the initial clusters is used.   This will provide for faster execution but
+less well separated initial clusters and hence possibly an inferior final
+result.

 
 

-The command uses an iterative algorithm to determine the clusters for
-each case.  It will continue iterating until convergence, or until @var{max_iter}
-iterations have been done.  The default value of @var{max_iter} is 2.
+
+@cmd{QUICK CLUSTER} uses an iterative algorithm to select the clusters centers.
+The subcommand  @subcmd{/CRITERIA=MXITER(@var{max_iter})} sets the maximum number of iterations.
+During classification, @pspp{} will continue iterating until until @var{max_iter}
+iterations have been done or the convergence criterion (see below) is fulfilled.
+The default value of @var{max_iter} is 2.
+
+If however, you specify @subcmd{/CRITERIA=NOUPDATE} then after selecting the initial centers,
+no further update to the cluster centers is done.  In this case, @var{max_iter}, if specified.
+is ignored.
+
+The subcommand  @subcmd{/CRITERIA=CONVERGE(@var{epsilon})} is used
+to set the convergence criterion.  The value of convergence criterion is  @var{epsilon}
+times the minimum distance between the @emph{initial} cluster centers.  Iteration stops when
+the  mean cluster distance between  one iteration and the next  
+is less than the convergence criterion.  The default value of @var{epsilon} is zero.

 
 The @subcmd{MISSING} subcommand determines the handling of missing variables.  
 If @subcmd{INCLUDE} is set, then user-missing values are considered at their face
 
 The @subcmd{MISSING} subcommand determines the handling of missing variables.  
 If @subcmd{INCLUDE} is set, then user-missing values are considered at their face


@@ -1575,6 +1860,12 @@ clustering variables contain missing values.  Otherwise it is clustered
 on the basis of the non-missing values.
 The default is @subcmd{LISTWISE}.
 
 on the basis of the non-missing values.
 The default is @subcmd{LISTWISE}.
 

+The @subcmd{PRINT} subcommand requests additional output to be printed.
+If @subcmd{INITIAL} is set, then the initial cluster memberships will
+be printed.
+If @subcmd{CLUSTER} is set, the cluster memberships of the individual
+cases will be displayed (potentially generating lengthy output).
+

 
 @node RANK
 @section RANK
 
 @node RANK
 @section RANK


@@ -1654,7 +1945,7 @@ RELIABILITY
 @end display
 
 @cindex Cronbach's Alpha
 @end display
 
 @cindex Cronbach's Alpha

-The @cmd{RELIABILTY} command performs reliability analysis on the data.
+The @cmd{RELIABILITY} command performs reliability analysis on the data.

 
 The @subcmd{VARIABLES} subcommand is required. It determines the set of variables 
 upon which analysis is to be performed.
 
 The @subcmd{VARIABLES} subcommand is required. It determines the set of variables 
 upon which analysis is to be performed.


@@ -1753,3 +2044,5 @@ exclude them.
 Cases are excluded on a listwise basis; if any of the variables in @var{var_list} 
 or if the variable @var{state_var} is missing, then the entire case will be 
 excluded.
 Cases are excluded on a listwise basis; if any of the variables in @var{var_list} 
 or if the variable @var{state_var} is missing, then the entire case will be 
 excluded.

+
+@c  LocalWords:  subcmd subcommand