STATISTC 697B - ST- Bayesian Statistics

Institution:

University of Massachusetts Amherst

Subject:

Description:

This course will introduce students to Bayesian data analysis, including modeling and computation. We will begin with a description of the components of a Bayesian model and analysis(including the likelihood, prior, posterior, conjugacy, non-informativeness, credible intervals, etc.), and illustrate these objects in simple models. We will then develop Bayesian approaches to more complicated models. The course will introduce Markov chain Monte Carlo methods, and students will have the opportunity to learn to use the WinBUGS and R open source statistical packages for computation.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.umass.edu

Phone Number:

(413) 545-0111

Regional Accreditation:

New England Association of Schools and Colleges

Calendar System:

Semester

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