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Python game shows experimental probability and theoretical probabilty used in MDM4UI course


I made this game using Python for MDM4UI - Grade 12 Mathematics of Data Management - course project of which purpose is to allow students the opportunity to demonstrate their understanding of permuations, combinations, experimental and theoretical probability, and discrete probability distributions. I believe this game would help students understand experimental and theoretical proability by actually running the game plenty of times.

Game Description

This is a game that user need to escape from the dungeon, where user do not know how it looks like.
Although user cannot see the map, here is the map anyway for better understanding!
If you run a game initially, you will see the below. Note that user needs to pay $5 to play a game. After paid that, you now need to choose one of operate options.

Manual Mode

If you chose manual mode, you now need to choose your direction - Left or Right - without knowing how the dungeon would look like.
However, once user meets a monster, user will lose the game and $5 that user paid previously. Or user can find (earn) a money - 5, 10, 15, 20 dollars - and then can escape from the dungeon, which means user win a game.
As you can see, manual mode is designed for experimental probabilty so that user can play a game with user's own decision for choosing left and right and get the result of the game.

Automatic Mode

Automatic mode is the same as the manual mode but now a game itself runs the game automatically by choosing left or right randomly as much as user wants to and shows the result such as how many times that user won or lose and how much money user earned or lose.
Automatic mode is for theoretical probability shows specific results including how many times user win and lose, how much money user earned and spent, user's profit, how many times user met a monster or $5 or $10 or $15 or $20.