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# 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.

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