# -*- coding: utf-8 -*-
"""
Created on Thu Jun 20 17:03:24 2019
@author: User
"""
# 《Python数据分析基础》中国统计出版社
#import numpy as np
from scipy import stats
import pandas as pd
import statsmodels.api as sm
battery = pd.read_csv(u'data\\ch6\\battery.csv',encoding = "gbk")
print(battery.head())
print("\n 用bartlett进行方差同性质检验")
print(stats.bartlett(battery[battery['tech']==1]['Endurance'],
battery[battery['tech']==2]['Endurance']))
print("\n 用 levene 进行方差同性质检验")
print(stats.levene(battery[battery['tech']==1]['Endurance'],
battery[battery['tech']==2]['Endurance']))
print("\n 以上结果显示两总体方差具有同质性")
print("\n 两独立样本均值的t检验:")
print(stats.ttest_ind(battery[battery['tech']==1]['Endurance'],
battery[battery['tech']==2]['Endurance'],
equal_var=True))
print("\n P<<0.01,拒绝原假设")
运行:
用bartlett进行方差同性质检验
BartlettResult(statistic=3.3228777945188592, pvalue=0.06832213694213818)
用 levene 进行方差同性质检验
LeveneResult(statistic=1.543714821763612, pvalue=0.21833338426451232)
以上结果显示两总体方差具有同质性
两独立样本均值的t检验:
Ttest_indResult(statistic=-2.9908265619140626, pvalue=0.0038722567339729993)
P<<0.01,拒绝原假设