Monte Carlo Simulation: Estimating Dice Probabilities

How can a few lines of random dice rolls estimate a probability you'd struggle to compute by hand?

Finger exercises

Short drills on what this video just taught. Write the code, run the checks, and reveal the answer only if you are stuck.

0 / 5 passed

Exercise 1 of 5

One roll of the die

The list dice below is the video's die: each string stands for its number of dots. Complete roll_die() so that each call rolls the die once, returning one face picked at random from dice. The random module's choice function will help. Define roll_die().

import random
dice = ['.',':',':.','::','::.',':::']

def roll_die():
    # Return one face of the die, chosen at random.
    return ...

import random
dice = ['.',':',':.','::','::.',':::']

def roll_die():
    # Return one face of the die, chosen at random.
    return ...

Python runs in your browser

⌘/Ctrl + Enter runs

returns a string

always returns one of the six faces

every face turns up over many rolls

←Previous Hash Collisions, Good Hash Functions, and Hashable Keys Next Simulating a Pool's Fill Time: Why Averages Mislead →