案例：

tt = (sm-m)/np.sqrt(sv/float(n)) # t-statistic for meanpval = 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-8from __future__ import divisionimport numpy as npfrom 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 = 20output = []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))

以上这篇python中p-value的实现方式就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。