Set the known variance to

:

Setting the known variance to

Automatic is equivalent to using the sample variance:

The result is the same but a warning is issued:

Specify a single common variance for two groups or give a list of variances:

For multivariate data, covariance matrices can be given:

A single group covariance:

Separate covariance matrices for each dataset:

Test

versus

:

The

-values are typically large when the mean is close to

:

The

-values are typically small when the location is far from

:

Using

Automatic is equivalent to testing for a mean of zero:

Test

versus

:

The

-values are typically large when mean is close to

:

The

-values are typically small when the location is far from

:

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

Alternatively, test against

:

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

:

Create a

HypothesisTestData object for repeated property extraction:

The properties available for extraction:

Extract some properties from a

HypothesisTestData object:

The

-value and test statistic:

Extract any number of properties simultaneously:

The

-value and test statistic:

Tabulate the test results:

Retrieve the entries from a test table for customized reporting:

Tabulate

-values or test statistics:

The

-value from the table:

The test statistic from the table: