Abstract #300647

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JSM 2003 Abstract #300647
Activity Number: 377
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract - #300647
Title: Discrete Markov Chain Monte Carlo: An Undergraduate Course
Author(s): George W. Cobb*+
Companies: Mt. Holyoke College
Address: Dept. of Math Statistics and Computer Science, South Hadley, MA, 01075,
Keywords: Markov chain Monte Carlo ; simulation ; statistics education
Abstract:

Markov Chain Monte Carlo (MCMC) has established itself as a powerful and flexible tool for solving a great variety of statistical problems. Unfortunately, the standard approach to teaching MCMC puts it beyond the reach of most undergraduates. I will describe an approach that serves as the basis for a course whose only prerequisite is linear algebra. This course introduces students to hypothesis testing via permutation tests, the Metropolis algorithm, Bayesian posterior distributions, and the Gibbs sampler. The key to doing without a probability or statistics prerequisite is to restrict attention to finite-state chains and to rely heavily on simulation. Versions of the course, supported by a grant from the NSF, have been taught at Mount Holyoke College (2001, 2003) and Villanova University (2002).

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