This is documentation for an old release of SciPy (version 0.7.). Read this page in the documentation of the latest stable release (version 1.15.1).
scipy.stats.shapiro¶
- scipy.stats.shapiro(x, a=None, reta=0)¶
Shapiro and Wilk test for normality.
Given random variates x, compute the W statistic and its p-value for a normality test.
If p-value is high, one cannot reject the null hypothesis of normality with this test. P-value is probability that the W statistic is as low as it is if the samples are actually from a normal distribution.
Output: W statistic and its p-value
- if reta is nonzero then also return the computed “a” values
- as the third output. If these are known for a given size they can be given as input instead of computed internally.
