Hypothesis Tests

t-test, F-test, chi-square goodness-of-fit test, and more

Statistics and Machine Learning Toolbox™ provides parametric and nonparametric hypothesis tests to help you determine if your sample data comes from a population with particular characteristics.

Distribution tests, such as Anderson-Darling and one-sample Kolmogorov-Smirnov, test whether sample data comes from a population with a particular distribution. Test whether two sets of sample data have the same distribution using tests such as two-sample Kolmogorov-Smirnov.

Location tests, such as z-test and one-sample t-test, test whether sample data comes from a population with a particular mean or median. Test two or more sets of sample data for the same location value using a two-sample t-test or multiple comparison test.

Dispersion tests, such as Chi-square variance, test whether sample data comes from a population with a particular variance. Compare the variances of two or more sample data sets using a two-sample F-test or multiple-sample test.

Determine additional features of sample data by cross-tabulating, conducting a run test for randomness, and determine the sample size and power for a hypothesis test.

Functions

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 adtest Anderson-Darling test chi2gof Chi-square goodness-of-fit test crosstab Cross-tabulation dwtest Durbin-Watson test with residual inputs fishertest Fisher’s exact test jbtest Jarque-Bera test kstest One-sample Kolmogorov-Smirnov test kstest2 Two-sample Kolmogorov-Smirnov test lillietest Lilliefors test runstest Run test for randomness
 friedman Friedman’s test kruskalwallis Kruskal-Wallis test multcompare Multiple comparison test ranksum Wilcoxon rank sum test sampsizepwr Sample size and power of test signrank Wilcoxon signed rank test signtest Sign test ttest One-sample and paired-sample t-test ttest2 Two-sample t-test ztest z-test
 ansaribradley Ansari-Bradley test barttest Bartlett’s test sampsizepwr Sample size and power of test vartest Chi-square variance test vartest2 Two-sample F-test for equal variances vartestn Multiple-sample tests for equal variances

Topics

Hypothesis Testing

Hypothesis testing is a common method of drawing inferences about a population based on statistical evidence from a sample.

Hypothesis Test Terminology

All hypothesis tests share the same basic terminology and structure.

Hypothesis Test Assumptions

Different hypothesis tests make different assumptions about the distribution of the random variable being sampled in the data.

Available Hypothesis Tests

View hypothesis tests of distributions and statistics.