MATH153 PO - Bayesian Statistics

When Offered: Offered by a Claremont Colleges Math Department on a rotating basis; Last offered Spring 2022
Instructor(s): A. Castillo; G. Chandler; J. Hardin
Credit: 1

An introduction to principles of data analysis and advanced statistical modeling using Bayesian inference. Topics include a combination of Bayesian principles and advanced methods; general, conjugate and noninformative priors, posteriors, credible intervals, Markov Chain Monte Carlo methods, and hierarchical models. The emphasis throughout is on the application of Bayesian thinking to problems in data analysis. Statistical software will be used as a tool to implement many of the techniques. Prerequisites: MATH 151 PO or by permission of the instructor; Recommended: MATH 058 PO.

Satisfies the following General Education Requirement(s), subject to conditions explained in the Degree Requirements section of this Catalog:
Area 5