STAT 341 - Bayesian Statistics

Institution:

Williams College

Subject:

Statistics

Description:

The probability of an event can be defined in two ways: (1) the long-run frequency of the event, or (2) the belief that the event will occur. Classical statistical inference is built on the first definition given above, while Bayesian statistical inference is built on the second. This course will introduce the student to methods in Bayesian statistics. Topics covered include: prior distributions, posterior distributions, conjugacy, and Bayesian inference in single-parameter, multi-parameter, and hierarchical models. The computational issues associated with each of these topics will also be discussed.

Credits:

3.00

Credit Hours:

Prerequisites:

Statistics 201 and Mathematics 211, or permission of instructor

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.williams.edu

Phone Number:

(413) 597-3131

Regional Accreditation:

New England Association of Schools and Colleges

Calendar System:

Four-one-four plan

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