Northwestern University 1 credit Statistics
Introduction to basic concepts and principles in Bayesian inference such as the prior, likelihood, posterior and predictive distributions, as well as an introduction to a variety of computational algorithms for Bayesian inference. Students learn how to develop, describe, implement and critique statistical models from a Bayesian perspective. Prerequisites: STAT 320-2 and STAT 301-2 or STAT 350-0 or ECON 381-2 or MATH 386-2 or consent of instructor.
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