Bayesian Inference and Modern Statistical Methods


Duke is known for the depth of its expertise in Bayesian statistics, a field that has only risen in popularity with the advent of greater computational and data resources. Augment your skills in Bayesian statistics in our popular course, with a focus on foundational theory and computational methods.

Principles of data analysis and advanced statistical modeling. Bayesian inference, prior and posterior distributions, multi-level models, model checking and selection, stochastic simulation by Markov Chain Monte Carlo. Prerequisite: Statistical Science 210 and (Statistical Science 230 or 240L) and Mathematics 202, 202D, 212, or 222. Prerequisite or corequisite: Mathematics 216, 218, or 221.

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