Test versus :

The -values are typically large when the mean is close to 0:

The -values are typically small when the mean is far from 0:

Using Automatic is equivalent to testing for a mean of zero:

Test versus :

The -values are typically large when the mean is close to μ₀:

The -values are typically small when the mean is far from μ₀:

Test whether the mean vector of a multivariate population is the zero vector:

Alternatively, test against {0.1,0,-0.05,0}:

Using Automatic applies the generally most powerful appropriate test:

The property "AutomaticTest" can be used to determine which test was chosen:

Test versus :

The -values are generally small when the locations are not equal:

The -values are generally large when the locations are equal:

Test versus :

The order of the datasets affects the test results:

Test whether the mean difference vector of two multivariate populations is the zero vector:

Alternatively, test against {1,0,-1,0}:

Perform a particular test for equal locations:

Any number of tests can be performed simultaneously:

Perform all tests appropriate to the data simultaneously:

Use the property "AllTests" to identify which tests were used:

Create a HypothesisTestData object for repeated property extraction:

The properties available for extraction:

Extract some properties from a HypothesisTestData:

The -value and test statistic from a -type test:

Extract any number of properties simultaneously:

The -value and test statistic from a Mann–Whitney test:

Tabulate the results from a selection of tests:

A full table of all appropriate test results:

A table of selected test results:

Retrieve the entries from a test table for customized reporting:

The -values are above 0.05, so there is not enough evidence to reject at that level:

Tabulate -values for a test or group of tests:

The -value from the table:

A table of -values from all appropriate tests:

A table of -values from a subset of tests:

Report the test statistic from a test or group of tests:

The test statistic from the table:

A table of test statistics from all appropriate tests:

A two-sided test is performed by default:

Test versus :

Perform a two-sided test or a one-sided alternative:

Test versus :

Test versus :

Test versus :

Perform tests with one-sided alternatives when μ₀ is given:

Test versus :

Test versus :

Set the maximum number of iterations to use for multivariate median-based tests:

By default, -values are computed using asymptotic test statistic distributions:

For univariate median-based tests, -values can be obtained using permutation methods:

Set the number of permutations to use:

By default, random permutations are used:

For some tests, the permutation result is exact:

The result is not affected by the number of permutations when exact tests are used:

For mean-based tests, the -value is exact under the assumptions of the test:

Set the seed used for generating random permutations:

Set the significance level for diagnostic tests:

By default, 0.05 is used:

Setting the significance level may alter which test is automatically chosen:

A median-based test would have been chosen by default:

The significance level is also used for "TestConclusion" and "ShortTestConclusion":

By default, normality and equal variance are tested when appropriate:

If assumptions are not checked, some test results may differ:

Diagnostics can be controlled as a group using All or None:

Verify all assumptions:

Check no assumptions:

Diagnostics can be controlled independently:

Assume normality and symmetry but check for equal variances:

Only check for normality:

Unlisted assumptions are not tested:

Normality is assumed:

The result is the same but a warning is issued:

Test assumption values can be explicitly set:

The sign test was previously chosen because the data is not normally distributed:

Bypassing diagnostic tests can save compute time:

It is often useful to bypass diagnostic tests for simulation purposes:

The assumptions of the test hold by design, so a great deal of time can be saved:

The results are identical: