Please note that we can also use the randn() function to generate random numbers from the normal distribution with a particular mu and sigma. For example, the following piece of Python code will generate 10000 random numbers from the normal distribution that has a mu = 10 and sigma = 2.

from numpy.random import randn

mu = 10
sigma = 2
X2 = sigma*randn(10000) + mu

The code will generate 10000 floating point random numbers from the normal distribution that has the mean 10 and standard deviation sigma = 2.

We can verify the same by plotting the distribution of the numbers using a histogram.

from numpy.random import randn
from matplotlib import pyplot
  
mu = 10
sigma = 2
X2 = sigma*randn(10000) + mu
  
pyplot.hist(X2, bins=100)
pyplot.savefig("randn-2.png")
pyplot.close()

The histogram will look like the following: