python毒酒检测_Turkey HSD检验法/W法

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python 2.7

# -*- coding: utf-8 -*-

from statsmodels.stats.multicomp import (pairwise_tukeyhsd,

MultiComparison)

# Import standard packages

import numpy as np

from scipy import stats

import pandas as pd

import variance_check

#数据excel名

excel="sample.xlsx"

#读取数据

df=pd.read_excel(excel)

#获取第一组数据，结构为列表

group_mentaln=list(df.StressReduction[(df.Treatment=="mental")])

group_physical=list(df.StressReduction[(df.Treatment=="physical")])

group_medical=list(df.StressReduction[(df.Treatment=="medical")])

list_groups=[group_mentaln,group_physical,group_medical]

list_total=group_mentaln+group_physical+group_medical

print"equal test-----------------------------------------------------"

# #比较组内的样本是否相等，如果不相等，不适合于tukey等方法

equal_lenth=variance_check.Equal_lenth(list_groups)

if equal_lenth==False:

print("the length of groups are not equal")

multiComp = MultiComparison(df['StressReduction'], df['Treatment'])

tukey=multiComp.tukeyhsd()

summary=multiComp.tukeyhsd().summary()

print(summary)

q=tukey.q_crit

print("q values:",q)

'''

q值

Out[41]: 3.5057698487864877

'''

'''

Multiple Comparison of Means - Tukey HSD,FWER=0.05

===============================================

group1 group2 meandiff lower upper reject

-----------------------------------------------

medical mental 1.5 0.3217 2.6783 True

medical physical 1.0 -0.1783 2.1783 False

mental physical -0.5 -1.6783 0.6783 False

-----------------------------------------------

'''

print("data details:",summary.data)

'''

[['group1', 'group2', 'meandiff', 'lower', 'upper', 'reject'],

[u'medical', u'mental', 1.5, 0.32169999999999999, 2.6783000000000001, True],

[u'medical', u'physical', 1.0, -0.17829999999999999, 2.1783000000000001, False],

[u'mental', u'physical', -0.5, -1.6782999999999999, 0.67830000000000001, False]]

'''

variance_check.py

# -*- coding: utf-8 -*-

'''

用于方差齐性检验

正太性检验

配对相等检验

'''

import scipy,math

from scipy.stats import f

import numpy as np

import matplotlib.pyplot as plt

import scipy.stats as stats

# additional packages

from statsmodels.stats.diagnostic import