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: 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.
See also
- anderson
- The Anderson-Darling test for normality
References
[R310] http://www.itl.nist.gov/div898/handbook/prc/section2/prc213.htm