Question 8 ML Assignment 1

Q8.py

import numpy as np
data=np.random.normal(5, 2**0.5, 1000)

split_data=np.split(data,10)

means=[]
variances=[]

for sd in split_data:
	means.append(np.mean(sd))
	variances.append(np.var(sd))

print means
print variances

bias=np.mean(means)
all_variance=np.mean(variances)

sums=0

for i in data:
	sums+=i-bias

print sums
print all_variance