问题
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)
The same example in R
returns:
> 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
What am I doing wrong?
Thanks
回答1:
For this chisq.test
call python equivalent is chi2_contingency:
This function computes the chi-square statistic and p-value for the hypothesis test of independence of the observed frequencies in the contingency table observed.
>>> 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)
来源:https://stackoverflow.com/questions/20492419/python-scipy-chisquare-returns-different-values-than-r-chisquare