Hypothesis tests give quantitative answers to common questions, such as how good the fit is between data and a particular distribution, whether these distributions have the same mean or median, and whether these datasets have the same variability.
Mathematica provides high-level functions for these types of questions and will automatically select the tests applicable for the data and distributions given. The high-level functions typically run more than one test and are able to produce full reports, but there are also specific named hypothesis tests such as the Kolmogorov-Smirnov goodness-of-fit test, or paired
-test. These give more direct control over settings and performance for specific tests.
DistributionFitTest — test for goodness-of-fit to a distribution of data
LocationTest — test means or mean differences of one or two datasets
LocationEquivalenceTest — compare means or medians of two or more datasets
VarianceTest — test variances or variance ratios of one or two datasets
VarianceEquivalenceTest — compare variances of two or more datasets
Options and Objects for Hypothesis Tests
HypothesisTestData — hypothesis test data generated by hypothesis tests
SignificanceLevel — significance level to use for reporting test conclusions
AlternativeHypothesis — alternative hypothesis for location and variance tests
VerifyTestAssumptions — whether to verify data assumptions through diagnostic tests
