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 asz-test and one-samplet-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-samplet-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-sampleF-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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Distribution Tests

`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`	两个示例Kolmogorov-Smirnovtest
`lillietest`	Lilliefors test
`runstest`	Run test for randomness

Location Tests

`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-samplet-test
`ttest2`	Two-samplet-test
`ztest`	z-test

Dispersion Tests

`ansaribradley`	Ansari-Bradley test
`barttest`	Bartlett’s test
`sampsizepwr`	Sample size and power of test
`vartest`	Chi-square variance test
`vartest2`	Two-sampleF-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.

Featured Examples

Selecting a Sample Size

Determine the number of samples or observations needed to carry out a statistical test. It illustrates sample size calculations for a simple problem, then shows how to use thesampsizepwrfunction to compute power and sample size for two more realistic problems. Finally, it illustrates the use of Statistics and Machine Learning Toolbox™ functions to compute the required sample size for a test that thesampsizepwrfunction does not support.

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