# AP Statistics Curriculum 2007 Bayesian Gibbs

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## Revision as of 06:02, 2 June 2009

Gibbs sampling is an algorithm to generate a sequence of samples from the joint probability distribution of two or more random variables. The purpose of this sequence is to approximate the joint distribution, or to compute an expected value. Gibbs sampling is a special case of the Metropolis-Hastings algorithm also making it an example of a Markov chain Monte Carlo algorithm.

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