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×Corpus Christi, Texas
3:0An introduction to Bayesian Statistics for scientists. Topics include: the Bayesian paradigm, with advantages and disadvantages; brief coverage of probability and calculus; basics of Markov Chain Monte Carlo methods, including the Gibbs sampler and the Metropolis-Hastings algorithm; validating, comparing, and interpreting Bayesian models; and examples from literature relevant to student interests. The course assumes no prior exposure to calculus or programming. FALL
Units: 3.0