# 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
 `meanEffectSize` One-sample or two-sample effect size computations `gardnerAltmanPlot` Gardner-Altman plot for two-sample effect size

#### Detect Drift

 `detectdrift` Detect drifts between baseline and target data using permutation testing

#### Access Test Results

 `DriftDiagnostics` Diagnostics information for batch drift detection

#### Examine Test Results

 `summary` Summary table for `DriftDiagnostics` object `ecdf` Compute empirical cumulative distribution function (ecdf) for baseline and target data specified for data drift detection `histcounts` Compute histogram bin counts for specified variables in baseline and target data for drift detection `plotDriftStatus` Plot p-values and confidence intervals for variables tested for data drift `plotEmpiricalCDF` Plot empirical cumulative distribution function (ecdf) of a variable specified for data drift detection `plotHistogram` Plot histogram of a variable specified for data drift detection `plotPermutationResults` Plot histogram of permutation results for a variable specified for data drift detection