scipy.stats.shapiro¶

scipy.stats.shapiro(x, a=None, reta=False)[source]¶

Perform the Shapiro-Wilk test for normality.

The Shapiro-Wilk test tests the null hypothesis that the data was drawn from a normal distribution.

Parameters:

Parameters:	x : array_like Array of sample data. a : array_like, optional Array of internal parameters used in the calculation. If these are not given, they will be computed internally. If x has length n, then a must have length n/2. reta : bool, optional Whether or not to return the internally computed a values. The default is False.
Returns:	W : float The test statistic. p-value : float The p-value for the hypothesis test. a : array_like, optional If reta is True, then these are the internally computed “a” values that may be passed into this function on future calls.

x : array_like

Array of sample data.

a : array_like, optional

Array of internal parameters used in the calculation. If these are not given, they will be computed internally. If x has length n, then a must have length n/2.

reta : bool, optional

Whether or not to return the internally computed a values. The default is False.

Returns:

W : float

The test statistic.

p-value : float

The p-value for the hypothesis test.

a : array_like, optional

If reta is True, then these are the internally computed “a” values that may be passed into this function on future calls.

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