python筆記：6.3.1獨立樣本均值之差假設檢驗（例6-7電池續航時間）

 

# -*- coding: utf-8 -*-
"""
Created on Thu Jun 20 17:03:24 2019

@author: User
"""


# 《Python數據分析基礎》中國統計出版社

#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進行方差同性質檢驗")
print(stats.bartlett(battery[battery['tech']==1]['Endurance'],
                     battery[battery['tech']==2]['Endurance']))

print("\n 用 levene 進行方差同性質檢驗")
print(stats.levene(battery[battery['tech']==1]['Endurance'],
                     battery[battery['tech']==2]['Endurance']))

print("\n 以上結果顯示兩總體方差具有同質性")

print("\n 兩獨立樣本均值的t檢驗：")
print(stats.ttest_ind(battery[battery['tech']==1]['Endurance'],
                      battery[battery['tech']==2]['Endurance'],
                      equal_var=True))

print("\n P<<0.01，拒絕原假設")

運行：

 用bartlett進行方差同性質檢驗
BartlettResult(statistic=3.3228777945188592, pvalue=0.06832213694213818)

 用 levene 進行方差同性質檢驗
LeveneResult(statistic=1.543714821763612, pvalue=0.21833338426451232)

 以上結果顯示兩總體方差具有同質性

 兩獨立樣本均值的t檢驗：
Ttest_indResult(statistic=-2.9908265619140626, pvalue=0.0038722567339729993)

 P<<0.01，拒絕原假設