Python scipy chisquare返回的值与R chisquare不同 [英] Python scipy chisquare returns different values than R chisquare

问题描述

我正在尝试使用scipy.stats.chisquare.我建立了一个玩具示例:

I am trying to use scipy.stats.chisquare. I have built a toy example:

In [1]: import scipy.stats as sps

In [2]: import numpy as np

In [3]: sps.chisquare(np.array([38,27,23,17,11,4]), np.array([98, 100, 80, 85,60,23]))
Out[11]: (240.74951271813072, 5.302429887719704e-50)

R中的相同示例返回:

> chisq.test(matrix(c(38,27,23,17,11,4,98,100,80,85,60,23), ncol=2))

Pearson's Chi-squared test

data:  matrix(c(38, 27, 23, 17, 11, 4, 98, 100, 80, 85, 60, 23), ncol = 2)
X-squared = 7.0762, df = 5, p-value = 0.215

我在做什么错了?

谢谢

推荐答案

对于此chisq.test调用，python等效项是

For this chisq.test call python equivalent is chi2_contingency:

此函数计算卡方统计量和p值，用于假设检验中独立于所观察频率 列联表 .

>>> arr = np.array([38,27,23,17,11,4,98,100,80,85,60,23]).reshape(2,-1)
>>> arr
array([[ 38,  27,  23,  17,  11,   4],
       [ 98, 100,  80,  85,  60,  23]])
>>> chi2, p, dof, expected = scipy.stats.chi2_contingency(arr)
>>> chi2, p, dof
(7.0762165124844367, 0.21503342516989818, 5)

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