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central limit theorem

2022-07-19 03:40:00 【elkluh】

The central limit theorem points out the condition that a large number of random variables approximately obey the normal distribution .

import numpy as np
import matplotlib.pyplot as plt
N = 1000
x1 = np.zeros(N)
print(x1.shape)
for n in range(N):
  x1[n] = np.sum(np.random.rand(12,1)) - np.sum(np.random.rand(12,1)) 
  
fig, ax = plt.subplots(figsize=(5,5))  #figuresize  Refers to the window size 
ax.hist(x1, 20)
plt.savefig('20.png')

np.random.rand() The resulting points are randomly distributed , It can be seen from the figure below that the point subtraction of random distribution conforms to the normal distribution , In fact, addition is also .