python中p-value的实现方式
人气:0案例:
tt = (sm-m)/np.sqrt(sv/float(n)) # t-statistic for mean pval = stats.t.sf(np.abs(tt), n-1)*2 # two-sided pvalue = Prob(abs(t)>tt) print 't-statistic = %6.3f pvalue = %6.4f' % (tt, pval) t-statistic = 0.391 pvalue = 0.6955
链接:
https://stackoverflow.com/questions/17559897/python-p-value-from-t-statistic
http://docs.scipy.org/doc/scipy/reference/tutorial/stats.html
可执行代码
# coding: utf-8 from __future__ import division import numpy as np from scipy import stats means = [0.0539, 4,8,3,6,9,1] stds = [5,4,8,3,6,7,9] mu = [0, 4.1, 7, 2, 5, 8, 0] n = 20 output = [] for sm, std, m in zip(means, stds, mu): # print("value:", sm, std) tt = (sm-m)/(std/np.sqrt(float(n))) # t-statistic for mean pval = stats.t.sf(np.abs(tt), n-1)*2 # two-sided pvalue = Prob(abs(t)>tt) # print('t-statistic = %6.3f pvalue = %6.4f' % (tt, pval)) output.append(format(pval)) print("\t".join(output))
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