https://github.com/kudosscience/let-s-make-a-deal
A Python Jupyter Notebook implementation of the game "Let's Make A Deal", famous for popularising the Monty Hall Problem
https://github.com/kudosscience/let-s-make-a-deal
Last synced: about 1 month ago
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A Python Jupyter Notebook implementation of the game "Let's Make A Deal", famous for popularising the Monty Hall Problem
- Host: GitHub
- URL: https://github.com/kudosscience/let-s-make-a-deal
- Owner: kudosscience
- Created: 2024-01-31T12:54:37.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2025-07-23T20:35:56.000Z (11 months ago)
- Last Synced: 2025-07-23T23:16:40.054Z (11 months ago)
- Language: Jupyter Notebook
- Size: 4.88 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 1
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Metadata Files:
- Readme: README.md
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README
# Let's Make a Deal
The Monty Hall problem is a probability puzzle named after Monty Hall, the original host of the game show "Let's Make a Deal". The problem goes like this:
You're on a game show, and there are three doors. Behind one door is a car, behind the others, goats. You choose a door, say No. 1.
Now the host, who knows what's behind the doors, opens another door, say No. 3, which has a goat. He then says to you, "Do you want to pick door No. 2?"
Is it to your advantage to switch your choice of doors?
Counter-intuitively, the answer is yes. If you switch doors, you have a 2/3 chance of winning the car, while if you stick to your initial choice, you have a 1/3 chance.
Intuitively most people believe that each of the 2 remaining doors has an equal probability.
However, the simulation in the attached Jupyter Notebook will show that switching is the better strategy.