X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;ds=sidebyside;f=doc%2Fstatistics.texi;h=b4cbcdd86b23c5ea217eb37a4d60e96d72e8ec89;hb=0b52efcb1226c05b87c4ff9add5c91c70c42c862;hp=9b4c3ed204cac599b5d6ede2b87c2c822cb291e2;hpb=2a063214a1869edf404a8d558c4a23e979ed829d;p=pspp diff --git a/doc/statistics.texi b/doc/statistics.texi index 9b4c3ed204..b4cbcdd86b 100644 --- a/doc/statistics.texi +++ b/doc/statistics.texi @@ -14,6 +14,7 @@ far. * NPAR TESTS:: Nonparametric tests. * T-TEST:: Test hypotheses about means. * ONEWAY:: One way analysis of variance. +* QUICK CLUSTER:: K-Means clustering. * RANK:: Compute rank scores. * REGRESSION:: Linear regression. * RELIABILITY:: Reliability analysis. @@ -38,7 +39,7 @@ DESCRIPTIVES @{A,D@} @end display -The @cmd{DESCRIPTIVES} procedure reads the active file and outputs +The @cmd{DESCRIPTIVES} procedure reads the active dataset and outputs descriptive statistics requested by the user. In addition, it can optionally compute Z-scores. @@ -360,7 +361,6 @@ CROSSTABS /MISSING=@{TABLE,INCLUDE,REPORT@} /WRITE=@{NONE,CELLS,ALL@} /FORMAT=@{TABLES,NOTABLES@} - @{LABELS,NOLABELS,NOVALLABS@} @{PIVOT,NOPIVOT@} @{AVALUE,DVALUE@} @{NOINDEX,INDEX@} @@ -418,11 +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 @@ -555,7 +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] ] @@ -600,6 +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 @@ -683,8 +680,12 @@ is used. * CHISQUARE:: Chisquare Test * 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 @@ -796,6 +797,62 @@ The Friedman test is used to test for differences between repeated measures when A list of variables which contain the measured data must be given. The procedure prints the sum of ranks for each variable, the test statistic and its significance. +@node KENDALL +@subsection Kendall's W Test +@vindex KENDALL +@cindex Kendall's W test +@cindex coefficient of concordance + +@display + [ /KENDALL = varlist ] +@end display + +The Kendall test investigates whether an arbitrary number of related samples come from the +same population. +It is identical to the Friedman test except that the additional statistic W, Kendall's Coefficient of Concordance is printed. +It has the range [0,1] --- a value of zero indicates no agreement between the samples whereas a value of +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 @@ -841,6 +898,58 @@ Cases for which the @var{var} value is neither @var{group1} or @var{group2} will The value of the Mann-Whitney U statistic, the Wilcoxon W, and the significance will be printed. The abbreviated subcommand M-W may be used in place of MANN-WHITNEY. +@node MCNEMAR +@subsection McNemar Test +@vindex MCNEMAR +@cindex McNemar test + +@display + [ /MCNEMAR varlist [ WITH varlist [ (PAIRED) ]]] +@end display + +Use McNemar's test to analyse the significance of the difference between +pairs of correlated proportions. + +If the @code{WITH} keyword is omitted, then tests for all +combinations of the listed variables are performed. +If the @code{WITH} keyword is given, and the @code{(PAIRED)} keyword +is also given, then the number of variables preceding @code{WITH} +must be the same as the number following it. +In this case, tests for each respective pair of variables are +performed. +If the @code{WITH} keyword is given, but the +@code{(PAIRED)} keyword is omitted, then tests for each combination +of variable preceding @code{WITH} against variable following +@code{WITH} are performed. + +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 @@ -848,7 +957,7 @@ The abbreviated subcommand M-W may be used in place of MANN-WHITNEY. @cindex runs test @display - [ /RUNS (@{MEAN, MEDIAN, MODE, value@}) varlist ] + [ /RUNS (@{MEAN, MEDIAN, MODE, value@}) = varlist ] @end display The /RUNS subcommand tests whether a data sequence is randomly ordered. @@ -1055,7 +1164,7 @@ ONEWAY /MISSING=@{ANALYSIS,LISTWISE@} @{EXCLUDE,INCLUDE@} /CONTRAST= value1 [, value2] ... [,valueN] /STATISTICS=@{DESCRIPTIVES,HOMOGENEITY@} - + /POSTHOC=@{BONFERRONI, GH, LSD, SCHEFFE, SIDAK, TUKEY, ALPHA ([value])@} @end display The @cmd{ONEWAY} procedure performs a one-way analysis of variance of @@ -1099,11 +1208,76 @@ A setting of EXCLUDE means that variables whose values are user-missing are to be excluded from the analysis. A setting of INCLUDE means they are to be included. The default is EXCLUDE. +Using the @code{POSTHOC} subcommand you can perform multiple +pairwise comparisons on the data. The following comparison methods +are available: +@itemize +@item LSD +Least Significant Difference. +@item TUKEY +Tukey Honestly Significant Difference. +@item BONFERRONI +Bonferroni test. +@item SCHEFFE +Scheff@'e's test. +@item SIDAK +Sidak test. +@item GH +The Games-Howell test. +@end itemize + +@noindent +The optional syntax @code{ALPHA(@var{value})} is used to indicate +that @var{value} should be used as the +confidence level for which the posthoc tests will be performed. +The default is 0.05. + +@node QUICK CLUSTER +@comment node-name, next, previous, up +@section QUICK CLUSTER +@vindex QUICK CLUSTER + +@cindex K-means clustering +@cindex clustering + +@display +QUICK CLUSTER var_list + [/CRITERIA=CLUSTERS(@var{k}) [MXITER(@var{max_iter})]] + [/MISSING=@{EXCLUDE,INCLUDE@} @{LISTWISE, PAIRWISE@}] +@end display + +The @cmd{QUICK CLUSTER} command performs k-means clustering on the +dataset. This is useful when you wish to allocate cases into clusters +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 @samp{/CRITERIA=CLUSTERS(@var{k})} where @var{k} is the +number of clusters. If this is not given, then @var{k} defaults to 2. + +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. + +The @cmd{MISSING} subcommand determines the handling of missing variables. +If INCLUDE is set, then user-missing values are considered at their face +value and not as missing values. +If EXCLUDE is set, which is the default, user-missing +values are excluded as well as system-missing values. + +If LISTWISE is set, then the entire case is excluded from the analysis +whenever any of the clustering variables contains a missing value. +If PAIRWISE is set, then a case is considered missing only if all the +clustering variables contain missing values. Otherwise it is clustered +on the basis of the non-missing values. +The default is LISTWISE. + @node RANK @comment node-name, next, previous, up @section RANK + @vindex RANK @display RANK