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.  0.2 0.4 0.3 0.1 0. ]
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:  [0.166204 0.166675 0.166508 0.166805 0.166883 0.166925]
1:  [0.166346 0.166416 0.166692 0.16667  0.166575 0.167301]
2:  [0.167064 0.167034 0.166341 0.166529 0.16689  0.166142]
3:  [0.166911 0.166304 0.166528 0.166351 0.167288 0.166618]

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

[0.275 0.15  0.15  0.15  0.1   0.175]