Monte Carlo methods are a class of computational algorithms, that rely on repeated random sampling. They can provide solutions to problems, that are otherwise untraceable or too complex to analyse mathematically.
Implementation
it is important not to overthink it, monte carlo simulations are very straight forward.
import numpy as np
def coinflip():
return np.random.randint(0,2)
def monte_carlo(n):
probabilities = []
avg_result = 0
for i in range(n):
flip_result = coinflip()
avg_result += flip_result
prob_value = avg_result/(i+1)
probabilities.append(prob_value)
avg_result /= n
return avg_result, probabilities
