4. Monte Carlo simulation. We can gain more insight into the nature of the Bernoulli distribution by doing a Monte Carlo simulation, that is, by using a computer to "flip coins" and average over many measurements. In the context of random walks, we can implement a N-step walk with the following python code import random import numpy as np def simulate_random_walk_length(n, p): # N is the number of steps # p is the probability that it moves to the right # (so 1-p is the probability that it moves to the left) # x holds the position of the walker at a given time x = 0 for i in range (N): rnd = random.random() if rnd