# Normality Tests Tab

Tests to determine if the sample data follows a normal distribution.

There are four types of normality tests depending on the number of variables selected.

Normality Test | Description
--- | ---
Anderson-Darling | Anderson-Darling (parameters assumed unknown): Select this option to compute the Anderson-Darling test of normality. The p-value is computed under the assumption that the parameters are unknown. Anderson-Darling (parameters assumed known): Select this option to compute the Anderson-Darling test of normality. The p-value is computed under the assumption that the parameters are known.
Kolmogorov-Smirnov test | KS test (parameters assumed unknown): Select this option to compute the Kolmogorov-Smirnov test of normality. The p-value is computed under the assumption that the parameters are unknown. KS test (parameters assumed known): Select this option to compute the Kolmogorov-Smirnov test of normality. The p-value is computed under the assumption that the parameters are known.
Shapiro-Wilk | Select this option to compute the Shapiro-Wilk normality test. This test is available for n up to 5,000.
Mardia multivariate normality test | If two or more variables are selected, then select this option to compute the Mardia multivariate normality tests based on multivariate skewness and kurtosis.

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