Question

Suppose that your enemy has a set of 20 weighted coins that each has a probability of 0.6 of landing heads when flipped. Estimate the mean number of heads if the set was flipped over and over by simulating 250,000 flips of the set and computing the average. (In python)

Answer 1

Python-code

import numpy as np

import random

coinoutcomes = ("H","T")
iterations = 20
simulations = 250000

allflips = []

random.seed(1453)

# function to return the randon value
# on biased biased coin FLIP
# since the probability of heads = 0.6, we have 3 heads and 2 tails in 5 items

def biasedcoin():
    return random.choice(['H','T','H','H','T'])

headsfound = np.zeros((simulations))
coinflips = 0
for j in range(0, simulations):
   
    temp = []
   
    for i in range(0,iterations) :
        temp.append(biasedcoin())

        if temp[i] == "H":
            headsfound[j] = headsfound[j] + 1
           
           
meanheads = np.mean(headsfound)
print("\nAverage heads found = ", meanheads)   

Python-output

Average heads found = 11.99912