The story
This project is Part 1 of a two-part project combining probability simulation and game logic implementation to analyze and build a digital version of the Mancala board game.The first part explores random number generation and probability convergence to simulate outcomes and model game randomness. The second part applies these insights to a Python implementation of Mancala, complete with turn logic, scoring, and an optional AI opponent.
In this project, I developed Python programs to generate random numbers and simulate probability scenarios. This project demonstrates understanding of pseudorandom number generation, reproducibility with seeds, and statistical analysis of generated data.
Stack: Python (random module).
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Key Contributions
- Implemented random number generation using Python’s built-in libraries.
- Applied randomization to simulate probabilistic experiments.
- Explored reproducibility with random seeds for consistent testing.
- Analyzed distributions and outcomes to validate statistical properties.
- Produced a clear write-up documenting methodology and results.
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Skills Demonstrated
- Python programming (random module, reproducibility)
- Probability & statistics fundamentals
- Simulation of probabilistic processes
- Documentation of methodology and results
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