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Lecture 16: Using Randomness to Solve Non-random Problems

Lecture 16: Using Randomness to Solve Non-random Problems

This video was recorded at 6.00SC Introduction to Computer Science and Programming, Spring 2011 . This lecture starts by defining normal (Gaussian), uniform, and exponential distributions. It then shows how Monte Carlo simulations can be used to analyze the classic Monty Hall problem and to find an approximate value of pi. Topics covered: Gaussian distributions, analytical models, simulations, exponential growth, probability, distributions, Monty Hall problem.

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