< Master index Index for ./freetb4matlab/statistics/tests >

Index for ./freetb4matlab/statistics/tests

Matlab files in this directory:

 anova% Perform a one-way analysis of variance (ANOVA). The goal is to test
 bartlett_test% Perform a Bartlett test for the homogeneity of variances in the data
 chisquare_test_homogeneity% Given two samples @var{x} and @var{y}, perform a chisquare test for
 chisquare_test_independence% Perform a chi-square test for independence based on the contingency
 cor_test% Test whether two samples @var{x} and @var{y} come from uncorrelated
 f_test_regression% Perform an F test for the null hypothesis rr * b = r in a classical
 hotelling_test% For a sample @var{x} from a multivariate normal distribution with unknown
 hotelling_test_2% For two samples @var{x} from multivariate normal distributions with
 kolmogorov_smirnov_test% Perform a Kolmogorov-Smirnov test of the null hypothesis that the
 kolmogorov_smirnov_test_2% Perform a 2-sample Kolmogorov-Smirnov test of the null hypothesis
 kruskal_wallis_test% Perform a Kruskal-Wallis one-factor 'analysis of variance'.
 manova% Perform a one-way multivariate analysis of variance (MANOVA). The
 mcnemar_test% For a square contingency table @var{x} of data cross-classified on
 prop_test_2% If @var{x1} and @var{n1} are the counts of successes and trials in
 run_test% Perform a chi-square test with 6 degrees of freedom based on the
 sign_test% For two matched-pair samples @var{x} and @var{y}, perform a sign test
 t_test% For a sample @var{x} from a normal distribution with unknown mean and
 t_test_2% For two samples x and y from normal distributions with unknown means
 t_test_regression% Perform an t test for the null hypothesis @code{@var{rr} * @var{b} =
 u_test% For two samples @var{x} and @var{y}, perform a Mann-Whitney U-test of
 var_test% For two samples @var{x} and @var{y} from normal distributions with
 welch_test% For two samples @var{x} and @var{y} from normal distributions with
 wilcoxon_test% For two matched-pair sample vectors @var{x} and @var{y}, perform a
 z_test% Perform a Z-test of the null hypothesis @code{mean (@var{x}) ==
 z_test_2% For two samples @var{x} and @var{y} from normal distributions with

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