Newer
Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
# exercise 4.1.2
from matplotlib.pyplot import (figure, title, subplot, plot, hist, show)
import numpy as np
# Number of samples
N = 200
# Mean
mu = 17
# Standard deviation
s = 2
# Number of bins in histogram
nbins = 20
# Generate samples from the Normal distribution
X = np.random.normal(mu,s,N).T
# or equally:
X = np.random.randn(N).T * s + mu
# Plot the samples and histogram
figure()
title('Normal distribution')
subplot(1,2,1)
plot(X,'x')
subplot(1,2,2)
hist(X, bins=nbins)
# Compute empirical mean and standard deviation
mu_ = X.mean()
s_ = X.std(ddof=1)
print("Theoretical mean: ", mu)
print("Theoretical std.dev.: ", s)
print("Empirical mean: ", mu_)
print("Empirical std.dev.: ", s_)
show()
print('Ran Exercise 4.1.2')