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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.

Keywords:: videolectures, ocwc, oec

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Science and Technology / Computer Science

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Material Type:: Presentation
Date Added to MERLOT:: February 10, 2015
Date Modified in MERLOT:: February 10, 2015
Author:: John Guttag, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, MIT
Submitter:: The Open Education Consortium
Primary Audience:: College General Ed, College Lower Division, College Upper Division
Technical Format:: Video

Mobile Compatibility:: Not specified at this time
Language:: English
Cost Involved:: No
Source Code Available:: No
Creative Commons:: This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States