STA 421 - Bayesian Data Analysis

Institution:

Grand Valley State University

Subject:

Description:

An introduction to Bayesian data analysis utilizing the Gibbs Sampler and Metropolis-Hastings algorithm (Markov Chain Monte Carlo method). Estimating posterior distribution parameters, evaluating model effectiveness, hypothesis testing, and bivariate regression modeling. Appropriate computer programs will be used for analysis of real data sets. Offered winter semesters on sufficient demand. Prerequisites: STA 312 and MTH 202

Credits:

3.00

Credit Hours:

Prerequisites:

Prerequisites: STA 312 and MTH 202

Corequisites:

Exclusions:

Level:

Instructional Type:

Other

Notes:

May have started spring/summer 2007 or earlier.

Additional Information:

Historical Version(s):

Institution Website:

www.gvsu.edu

Phone Number:

(616) 331-2020

Regional Accreditation:

North Central Association of Colleges and Schools

Calendar System:

Semester

The Course Profile information is provided and updated by third parties including the respective institutions. While the institutions are able to update their information at any time, the information is not independently validated, and no party associated with this website can accept responsibility for its accuracy.