Test some data for normality:

The

-values for the normally distributed data are typically large:

The

-values for data that is not normally distributed are typically small:

Set the third argument to

Automatic to apply a generally powerful and appropriate test:

The property

can be used to determine which test was chosen:

Test whether data fits a particular distribution:

There is insufficient evidence to reject a good fit to a

WeibullDistribution:

Test for goodness of fit to a derived distribution:

The

-value is large for the mixture data compared to data not drawn from the mixture:

Test for goodness of fit to a formula-based distribution:

Unspecified parameters will be estimated from the data:

The

-value is dependent on which parameters were estimated:

Test some data for multivariate normality:

The

-values for normally distributed data are typically large compared to non-normal data:

Test some data for goodness of fit to a particular multivariate distribution:

Compare the distributions of two datasets:

The sample sizes need not be equal:

Compare the distributions of two multivariate datasets:

The

-values for equally distributed data are large compared to unequally distributed data:

Perform a particular goodness-of-fit test:

Any number of tests can be performed simultaneously:

Perform all tests, appropriate to the data and distribution, simultaneously:

Use the property

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 object:

The

-value and test statistic from a Cramér-von Mises test:

Extract any number of properties simultaneously:

The results from the Anderson-Darling

-value and test statistic:

Obtain the fitted distribution when parameters have been unspecified:

Extract the parameters from the fitted distribution:

Plot the PDF of the fitted distribution against the data:

Confirm the fit with a goodness-of-fit test:

The test distribution is returned when the parameters have been specified:

Visually compare the data to the fitted distribution:

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 normality 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: