t检验的代码
#coding=utf-8
"""
@author=wanggang
data=2020.10.30
"""
from scipy.stats import ttest_1samp
import numpy as np
from scipy.stats import ttest_ind, norm, f
import numpy as np
def read():
sample=[]
"""
def ftest(s1, s2):
'''F检验样本总体⽅差是否相等'''
print("Null Hypothesis:var(s1)=var(s2)，α=0.05")
F = np.var(s1) / np.var(s2)
v1 = len(s1) - 1
v2 = len(s2) - 1
p_val = 1 - 2 * abs(0.5 - f.cdf(F, v1, v2))
print(p_val)
if p_val < 0.05:
print("Reject the Null Hypothesis.")
html代码转链接
equal_var = False
else:
print("Accept the Null Hypothesis.")
equal_var = True
return equal_var
def ttest_ind_fun(s1, s2):
'''t检验独⽴样本所代表的两个总体均值是否存在差异'''
equal_var = ftest(s1, s2)
print("Null Hypothesis:mean(s1)=mean(s2)，α=0.05")
ttest, pval = ttest_ind(s1, s2, equal_var=equal_var)
if pval < 0.05:
print("Reject the Null Hypothesis.")
else:
print("Accept the Null Hypothesis.")
return pval
"""
#np.random.seed(42)
#s1 = norm.rvs(loc=1, scale=1.0, size=20)
#s2 = norm.rvs(loc=1.5, scale=0.5, size=20)
#s3 = norm.rvs(loc=1.5, scale=0.5, size=25)
#ttest_ind_fun(s1, s2)
#ttest_ind_fun(s2, s3)
print("原假设：假设⾮专业均值和总体的相等")
print("备择假设：假设⾮专业的均值不等于总体的均值")
print("Null Hypothesis:µ=µ0=30，α=0.05")
ages = [25,36,15,40,28,31,32,30,29,28,27,33,35]
t = (np.mean(ages)-30)/(np.std(ages,ddof=1)/np.sqrt(len(ages)))#这⾥的30 为总体的平均值 ddof=1 是计算的标准差。np.sqrt(len(ages))这个是
ttest,pval = ttest_1samp(ages,30)#计算p 值
#print(t,ttest)
if pval < 0.05:
print("拒绝原假设，备择假设成⽴。存在显著性差异")
else:
print("接收原假设，不存在显著性差异")

版权声明：本站内容均来自互联网，仅供演示用，请勿用于商业和其他非法用途。如果侵犯了您的权益请与我们联系QQ:729038198，我们将在24小时内删除。