The following Matlab project contains the source code and Matlab examples used for wilcoxon rank sum test and box plots for genes compounds etc in healthy vs. disease. Perform a Wilcoxon rank-sum test or Mann-Whitney U-test (non-parametric test).

The following Matlab project contains the source code and Matlab examples used for power and hypothesis testing for difference between two variances. . Estimates the power and the hypothesis testing for difference between two variances.

The following Matlab project contains the source code and Matlab examples used for tukey's test of additivity for a two-way classification analysis of variance. . Tukey's test of additivity for a two-way analysis of variance design with replication (can be equal or unequal sample sizes) or without replication.

The following Matlab project contains the source code and Matlab examples used for power estimation of a performed z test about mean(s). . Estimates the statistical power of a performed Z test about mean(s). It recalls you the statistical result of the test you should have arrived. It only needs the Z statistic, specified direction and significance level (default = 0.05).

The following Matlab project contains the source code and Matlab examples used for sample size in tests for difference between two variances. . Sample size required to achieve a specified test for difference between two variances, using the normal approximation.

The following Matlab project contains the source code and Matlab examples used for single-factor analysis of variance test. . Computes the single-factor Analysis of Variance Model I or Model II for equal or unequal sample sizes.

The following Matlab project contains the source code and Matlab examples used for kruskal-wallis' nonparametric analysis of variance. . Kruskal-Wallis' nonparametric analysis of variance test the difference among groups and it is applicable for equal or unequal sample sizes and if there are tied ranks. This file uses both the chi-squared and F approximations.

The following Matlab project contains the source code and Matlab examples used for single-factor analysis of variance test using only means and variances. . Computes a single-factor analysis of variances test using only means and variances(without data).

The following Matlab project contains the source code and Matlab examples used for bartlett's test for homogeneity of variances. . Bartlett's test is developed to estimate whether more than two groups are homoscedastic. Bartlett's statistic is approximated by the chi-square distribution. The file needs the data matrix and the significance level.

The following Matlab project contains the source code and Matlab examples used for cochran's cumulative distribution function. . Gives the p-value associated to the Cochran's statistics ratio of the largest S^2 to their total (max(S^2)/sum(S^2)). Function needs the Cochran's C statistic, the k variances and the v sample degrees of freedom.

The following Matlab project contains the source code and Matlab examples used for o'brien's test for homogeneity of variances. . In the Obrien's test to check out the homogeneity of variances the data are transforming to yij = ((nj-1.5)*nj*((xij-mean(xj))**2)-((0.5)*(var(xj))*(nj-1)))/((nj-1)*(nj-2)) and uses the F distribution performing an one-way ANOVA using y as the dependent variable.

The following Matlab project contains the source code and Matlab examples used for levene's test for homogeneity of variances. . Levene's F test is used to test the null hypothesis that multiple population variances corresponding to multiplesamples are equal.

The following Matlab project contains the source code and Matlab examples used for welch's test for homogeneity of variances. . Welch's test is developed to estimate whether more than two groups are homoscedastic. Also the Welch's test can be used as an alternative analysis of variance when samples variances are unequal.

The following Matlab project contains the source code and Matlab examples used for calulation of the a priori statistical power of a one-way manova test. . This file estimates the a priori statistical power of a single-factor Multivariate Analysis of Variance (MANOVA).

The following Matlab project contains the source code and Matlab examples used for computes a multivariate analysis of variance for equal or unequal sample sizes. . Computes a Multivariate Analysis of Variance for equal or unequal sample sizes.

The following Matlab project contains the source code and Matlab examples used for computes a two-way multivariate analysis of variance for equal or unequal sample sizes. . Computing of a two-way multivariate analysis of variance for equal or unequal sample sizes by the testing of the mean differences in several variables among several samples with two factors.

The following Matlab project contains the source code and Matlab examples used for conover's two sample squared ranks test for equality of variance. Performs the nonparametric squared ranks test on quality of variance for two samples.

The following Matlab project contains the source code and Matlab examples used for repeated measures two-way analysis of variance test. . ANOVA with two within-subject variables is used to analyze the relationship between two independent variables and the dependent variable.

The following Matlab project contains the source code and Matlab examples used for repeated measures mixed two-way analysis of variance test. . ANOVA with between- and within- subject variables (mixed) is used to analyze the relationship for designs that have a combination of between and within-subject variables.

The following Matlab project contains the source code and Matlab examples used for approximate test of equality of means when variances are heterogeneous. . Games-Howell's approximate test of equality of means from normal population when variances are heterogeneous.

The following Matlab project contains the source code and Matlab examples used for kolmogorov distribution functions. Add to Your statistic toolbox this functions: KolmCdf - Kolmogorov cumulative distribution function: F(x)=sum((-1)^n*exp(-2*n^2*x^2),n,-inf,inf); KolmPdf - Kolmogorov probability distribution function; KolmInv - Inverse of the Kolmogorov cumulative distribution function.

The following Matlab project contains the source code and Matlab examples used for barnard's exact probability test. . This file, as the Fisher's exact test, performs the exact probability test for a table of frequency data cross-classified according to two categorical variables, each of which has two levels or subcategories (2x2).

The following Matlab project contains the source code and Matlab examples used for cochran's q test for margins homogeneity. . This m-file performs the Cochran's Q test for multi-way tables which each variable has two levels, that is, for 2x2.

The following Matlab project contains the source code and Matlab examples used for anova and variance components for genetic data. These files are an adaptation of the ANOVA variance component estimators to be used in the analysis of genetic data, specifically Cockerham's 1969 Theta.

The following Matlab project contains the source code and Matlab examples used for statistical power of a performed (a posteriori) single-factor manova. . Estimating of the statistical power of a performed (a posteriori) single factor Multivariate Analysis of Variance (MANOVA).

The following Matlab project contains the source code and Matlab examples used for power analysis for t tests. The main function, TPOWER, will compute the power of a t-test given an effect size (d), sample size (N), and alpha.

The following Matlab project contains the source code and Matlab examples used for identification of outliers in a one-way analysis of variance model ii (random effects). . In a one-way analysis of variance random effects model one would expect that the measurements lie close together because the same quantity was measured and states that the class effects stem from a common source and therefore should not difer too much.

The following Matlab project contains the source code and Matlab examples used for three-way analysis of variance with repeated measures on two factors test. . This is a three-factor analysis of variance design in which there are repeated measures on two of the factors.