Chi Square 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). It is a non-parametric statistical test used to determine if there are nonrandom...

Usage: [p, Q]= chi2test(x) The chi-squared test.Given a number of samples this function tests the hypothesis that the samples areindependent. If Q > chi2(p, nu), the hypothesis is rejected. Each column represents a variables, each row a sample. If you find any errors, please let me know: ....

Sample size required in tests concerning the variance, employing the Chi-square distribution and solved by iterative fashion (directed trial and error). This means that we enter an initial value for n in order to obtain a better estimate. It only needs the sample variance, expected (hypothesized)...


Platforms: Matlab

This file performs the Fisher 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). It is a non-parametric statistical test used to determine if there are nonrandom associations between...


Platforms: Matlab

Statistics::ChiSquare - How well-distributed is your data? SYNOPSIS use Statistics::Chisquare; print chisquare(@array_of_numbers); Statistics::ChiSquare is available at a CPAN site near you. Suppose you flip a coin 100 times, and it turns up heads 70 times. Is the coin fair? Suppose...


Platforms: *nix

Statistics software for data analysis and multivariate statistical analysis. Probability analysis. Compute descriptive statistics of selected data. Frequency analysis. Compare means and variances. Variance analysis. Z test. Correlation tests. Jarque Bera test. Non-parametric tests, including...


Platforms: Windows, Windows 7, Windows Server

A statistical analysis used for count data is to compare the proportions of a binary outcome of interest for two or more groups.This m-file it is an implemented alternative to the Marascuillo's test and identifies significant pairwise contrasts that this last one does not. If the previously...


Platforms: Matlab

In the analysis of designed experiments, the Friedman test is the most common non-parametric test for complete block designs. The Durbin test is a nonparametric test for balanced incomplete designs that reduces to the Friedman test in the case of a complete block design.In a randomized block...


Platforms: Matlab

WINKS (Windows KWIKSTAT) makes statistical data analysis understandable and easy to perform for the researcher, student, or scientist. Top award-winning shareware statistics program with thousands of users in over 65 countries. Basic analyses available in WINKS include Descriptive statistics and...


Platforms: Windows

The Hardy Weinberg equilibrium is a fundamental law in genetic.This function was deeply rewrited.If a locus is biallelic the function use the exact Hardy Weinberg test (similar to Fisher exact test) analyzing all possible tables. If you download TERNPLOT functions (ID:2299) the function plots a...


Platforms: Matlab

In statistics, McNemar's test is a non-parametric method used on nominaldata to determine whether the row and column marginal frequencies are equal. It is named after Q. McNemar, who introduced it in 1947. It is applied to 2x2 contingency tables with a dichotomous trait with matched pairs of...


Platforms: Matlab

Fisher's exact test of 2x2 contingency tables permits calculation of precise probabilities in situation where, as a consequence of small cell frequencies, the much more rapid normal approximation and chi-square calculations are liable to be inaccurate.The Fisher's exact test involves the...


Platforms: Matlab

FISHERTEST - Fisher Exact test for 2-x-2 contingency tables H = FISHERTEST(M) performs the non-parametric Fisher exact probability test on a 2-by-2 contingency table described by M, and returns the result in H. It calculates the exact probability of observing the given and more extreme...


Platforms: Matlab

The Friedman test is a non-parametric statistical test developed by the U.S. economist Milton Friedman. Similar to the parametric repeated measures ANOVA, it is used to detect differences in treatments across multiple test attempts. The procedure involves ranking each row (or block) together,...


Platforms: Matlab

Fisher's exact test of 2x4 contingency tables permits calculation of precise probabilities in situation where, as a consequence of small cell frequencies, the much more rapid normal approximation and chi-square calculations are liable to be inaccurate. The Fisher's exact test involves the...


Platforms: Matlab

Fisher's exact test of 2x3 contingency tables permits calculation of precise probabilities in situation where, as a consequence of small cell frequencies, the much more rapid normal approximation and chi-square calculations are liable to be inaccurate. The Fisher's exact test involves the...


Platforms: Matlab

Fisher's exact test of 3x3 contingency tables permits calculation of precise probabilities in situation where, as a consequence of small cell frequencies, the much more rapid normal approximation and chi-square calculations are liable to be inaccurate. The Fisher's exact test involves the...


Platforms: Matlab

Other hypothesis used with the Mauchly's sphericity test is on the orthonormalized contrasts,H0: Cd-deOaoSC = s^2I , where C is any full-rank (p-1) x p matrix of orthonormal contrasts.A is the nonorthonormalized contrasts matrix.C = GMO(Ad-deOao) is a (p-1) doOCo p column-orthonormal matrix (by...


Platforms: Matlab

Doornik-Hansen (1994) introduce a multivariate version of the univariate omnibus test for normality of Shenton and Bowman (1977), based on the transformed skewness and kurtosis. Due that the skewness and kurtosis are not independently distributed and the kurtosis approaches very slowly to...


Platforms: Matlab

Grubb's outlier test can be used to remove one outlier (see deleteoutliers.m by Brett Schoelson). If you decide to remove this outlier, you might be tempted to run Grubbs' test again to see if there is a second outlier in your data. However, if you do this, you cannot use the same rejection...


Platforms: Matlab