scipy stats.normaltest()函数| Python

scipy.stats.normaltest(array, axis=0)函数测试样本是否不同于正态分布。此函数检验样本所来自的总体的零假设。

Parameters :
array : Input array or object having the elements.
axis : Axis along which the normal distribution test is to be computed. By default axis = 0.

Returns : k2 value and P-value for the hypothesis test on data set.

代码#1：

# Performing normaltest
from scipy.stats import normaltest
import numpy as np 
import pylab as p 
  
x1 = np.linspace( -5, 5, 1000 )
y1 = 1./(np.sqrt(2.*np.pi)) * np.exp( -.5*(x1)**2  )
  
p.plot(x1, y1, '.')
  
print( '\nNormal test for given data :\n', normaltest(y1))

输出 ：

给定数据的正常测试：NormaltestResult(statistic=146.08066794511544, pvalue=1.901016994532079e-32)

代码#2：

# Performing normaltest
from scipy.stats import normaltest
import numpy as np 
import pylab as p 
  
x1 = np.linspace( -5, 12, 1000 )
y1 = 1./(np.sqrt(2.*np.pi)) * np.exp( -.5*(x1)**2  )
  
p.plot(x1, y1, '.')
  
print( '\nNormal test for given data :\n', normaltest(y1))

输出 ：

给定数据的正常测试：NormaltestResult(statistic=344.05533061429884, pvalue=1.9468577593501764e-75)