Null Hypothesis

This simple function tests the null hypothesis that two variables are equally linearly correlated with a third variable when all three sets of observations were derived from the same "individuals" (i.e., a repeated measures/paired observations design). The test uses a t-distribution and was taken...

H = TRIPLESTEST(X) performs the non-parametric triples test for symmetry (skewness) of the null hypothesis that the data in X comes from a symmetrical distribution with an unknown median. The test involves the examination of subsets of three variables from X (triples) to determine the likelihood...

CHI2RAYLTEST: Single sample Pearson Chi Square goodness-of-fit statistical test to examine a null hypothesis of Rayleigh Channel.H=CHI2RAYLTEST(X,ALPHA) performs the particular case of Pearson Chi Squaretest to determine whether the null hypothesis of a Rayleigh channel realization is a...


Platforms: Matlab

Levene's F test is used to test the null hypothesis that multiple population variances corresponding to multiplesamples are equal. Prior to the analysis the data are transforming to the absolute deviation of the mean. Then perform an one-way analysis of variance.


Platforms: Matlab

Permutation test of the null hypothesis that a set of data was sampled from a symmetric distribution with a particular mean. The test is based on a t-statistic and can be applied to situations in which a one sample or paired sample/repeated measures t-test is appropriate. Note, that this test is...


Platforms: Matlab

CHI2TEST: Single sample Pearson Chi Square goodness-of-fit hypothesis test.H=CHI2TEST(X,ALPHA) performs the particular case of Pearson Chi Square test to determine whether the null hypothesis of composite normality PDF is a reasonable assumption regarding the population distribution of a random...


Platforms: Matlab

GRANGER_CAUSE is a Granger Causality Test. The null hypothesis is that the y does not Granger Cause x. A user specifies the two series, x and y, along with the significance level and the maximum number of lags to be considered. The function chooses the optimal lag length for x and y based on the...


Platforms: Matlab

Comparison of two survival curves can be done using a statistical hypothesis test called the log rank test. It is used to test the null hypothesis that there is no difference between the population survival curves (i.e. the probability of an event occurring at any time point is the same for each...


Platforms: Matlab

The Anderson-Darling test (Anderson and Darling, 1952) is used to test if a sample of data comes from a specific distribution. It is a modification of the Kolmogorov-Smirnov (K-S) test and gives more weight to the tails than the K-S test. The K-S test is distribution free in the sense that the...


Platforms: Matlab

H = COCHRANQTEST(X) performs the non-parametric Cochran's Q-test on the hypothesis that the K columns of N-by-K matrix have the same number of successes and failures. H==0 indicates that the null hypothesis cannot be rejected at the 5 significance level. H==1 indicates that the null hypothesis...


Platforms: Matlab

Compares probabilities of two binomial samples X, Y from a Bernoully experiments with probability p1 for set X and p2 for set YTest the null hypothesis H_0: p1 = p2 vs alternatives H_1: p1 > p2 H_2: p1 < p2 H_3: p1 != p2 Input: X - row of 0 or 1 Y - row of 0 or 1 Output: z - normal statistics...


Platforms: Matlab

As you know, the Student t-test can be used only to compare two groups. When you have k groups you can't use a t-test for each couple because, if you have fixed alpha=0.05 for each t-test, there is a probability of k*0.05 to find a difference when it isn't (Bonferroni inequality).The Holm-Sidak...


Platforms: Matlab

This function provides a Wilcoxon-type test for trend across a group of three or more independent random samples.Assumptions:- Data must be at least ordinal- Groups must be selected in a meaningful order i.e. orderedIf you do not choose to enter your own group scores then scores are allocated...


Platforms: Matlab

Anderson and Darling (1952, 1954) introduced a goodness-of-fit statistic to test the hypothesis that a random sample comes from a continuous population with a specified distribution function. It is a modification of the Kolmogorov-Smirnov (K-S) test and gives more weight to the tails than the K-S...


Platforms: Matlab

Single sample Smirnov-Cramer-Von Mises goodness-of-fit hypothesis test.H = MTEST(X,ALPHA) performs the particular case of Smirnov-Cramer-Von Mises test to determine whether the null hypothesis of composite normality CDF is a reasonable assumption regarding the population distribution of a random...


Platforms: Matlab

Single Sample Kupier Goodness-Of-Fit Hypothesis Test. Similar to Kolmogorov-Smirnov (K-S) test, but (K-S) test tend to be most sensitive around median value of the distribution and less sensitive at the distribution tails.Doesn't require any Toolbox.Find if the random sample X could have the...


Platforms: Matlab

This file performs the Stuart-Maxwell's test for all the marginal homogeneity (i.e. across all the categories simultaneously) for each of the two sample times (nominal samples). Obviously, it need a square KxK table.It is a non-parametric statistical test. The test was proposed by Stuart (1955),...


Platforms: Matlab

This m-file performs the Cochran's Q test for multi-way tables which each variable has two levels, that is, for 2x2...x2 tables. It is used to test the homogeneity of the one-dimensional margins. So, Cochran's Q test is a nonparametric test examining change in a dichotomous variable across more...


Platforms: Matlab

GTEST: Single sample Geary goodness-of-fit hypothesis test.H=GTEST(X,ALPHA) performs the Geary test to determine whether the null hypothesis of composite normality PDF is a reasonable assumption regarding the population distribution of a random sample X with the desired significance level ALPHA.H...


Platforms: Matlab

The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is unknown or where sample sizes are small. Their...


Platforms: Matlab