#!/usr/bin/env python

from numpy.random import seed
from numpy.random import randn
from numpy import mean
from numpy import std
from scipy.stats import ttest_ind
from scipy.stats import ttest_rel
from scipy.stats import f_oneway

seed(1)

# generate two sets of univariate observations
data1 = 5 * randn(100) + 50
data2 = 5 * randn(100) + 51

# summarize
print('data1: mean=%.3f std=%.3f' % (mean(data1), std(data1)))
print('data2: mean=%.3f std=%.3f' % (mean(data2), std(data2)))

# Student's t-test
stat, p = ttest_ind(data1, data2)

print('Statistics=%.3f, p=%.3f' % (stat, p))

# interpret
alpha = 0.05

if p > alpha:
	print('Same distributions (fail to reject H0)')
else:
	print('Different distributions (reject H0)')


# Paired Student's t-test

seed(1)
data1 = 5 * randn(100) + 50
data2 = 5 * randn(100) + 51

# compare samples
stat, p = ttest_rel(data1, data2)

print('Statistics=%.3f, p=%.3f' % (stat, p))

# interpret
alpha = 0.05

if p > alpha:
	print('Same distributions (fail to reject H0)')
else:
	print('Different distributions (reject H0)')

# Paired Student's t-test

seed(1)
data1 = 5 * randn(100) + 50
data2 = 5 * randn(100) + 51

# compare samples
stat, p = ttest_rel(data1, data2)
print('Statistics=%.3f, p=%.3f' % (stat, p))
# interpret
alpha = 0.05
if p > alpha:
	print('Same distributions (fail to reject H0)')
else:
	print('Different distributions (reject H0)')

# Analysis of Variance test

seed(1)
data1 = 5 * randn(100) + 50
data2 = 5 * randn(100) + 50
data3 = 5 * randn(100) + 52

# compare samples
stat, p = f_oneway(data1, data2, data3)

print('Statistics=%.3f, p=%.3f' % (stat, p))

# interpret
alpha = 0.05

if p > alpha:
	print('Same distributions (fail to reject H0)')
else:
	print('Different distributions (reject H0)')