Trials

Faisal Qureshi
faisal.qureshi@ontariotechu.ca
http://www.vclab.ca

Copyright information

© Faisal Qureshi

License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

import numpy as np

def dice_throw():
    return np.random.choice([1,2,3,4,5,6])

def estimate_dice_probabilities(num_throws):
    outcomes = np.zeros(6)
    for i in range(num_throws):
        outcome = dice_throw()
        outcomes[outcome-1] = outcomes[outcome-1] + 1
    return outcomes / num_throws

num_trials = 10
probabilities = estimate_dice_probabilities(num_trials)

print('probabilities:', probabilities)
print('true probabilities:', np.ones(6)/6.)

probabilities: [0.2 0.1 0.3 0.2 0.  0.2]
true probabilities: [0.16666667 0.16666667 0.16666667 0.16666667 0.16666667 0.16666667]

n_independent_trials = 4
probabilities = []
for i in range(n_independent_trials):
    num_throws = 1000000
    probabilities.append(estimate_dice_probabilities(num_throws))
    print(f'{i}: ', probabilities[-1])

0:  [0.166501 0.166531 0.167105 0.166554 0.166607 0.166702]
1:  [0.166105 0.16654  0.16658  0.167204 0.16695  0.166621]
2:  [0.166382 0.16646  0.166546 0.16692  0.166458 0.167234]
3:  [0.167432 0.166031 0.166604 0.167425 0.16602  0.166488]

sum = 0
for i in range(len(probabilities)):
    sum = sum + probabilities[i]    
print(sum/len(probabilities))

[0.166605   0.1663905  0.16670875 0.16702575 0.16650875 0.16676125]