Python Central Limit Theorem

central_limit_theorem.py

import numpy as np
import random


# Create a parent distribution, from the gamma family
shape, scale = 2., 2.  # mean=4, std=2*sqrt(2)
s = np.random.gamma(shape, scale, 100000)
print(np.mean(s))
import matplotlib.pyplot as plt
import scipy.special as sps
plt.hist(s)
plt.show()


# The distribution of the means from the sampled groups is normally distributed
samples = [ np.mean(random.choices(s, k=20)) for _ in range(1000) ]
plt.hist(samples)
plt.show()