140.763.01 BAYESIAN METHODS II
- 4th term
- 3 credits
- Academic Year:
- 2012 - 2013
- East Baltimore
- Class Times:
- Tu Th, 1:30 - 2:50pm
Builds upon the foundation laid in Bayesian Methods I (140.762). Discusses further current approaches to Bayesian modeling and computation in statistics. Describes and develops models of increasing complexity, including linear regression, generalized linear mixed effects, and hierarchical models. Acquaints students to advanced tools for fitting Bayesian models, including non-conjugate prior models. Includes examples of real statistical analyses.
- Learning Objectives:
- develop Bayesian models for the analysis of complex problems, including repeated measurement data and latent data models;
- create computer programs to run analyses;
- calculate posterior distributions of parameters of scientific interest;
- conduct Bayesian analyses of complex data sets.
- Methods of Assessment:
Student evaluation based on homework and a final project.
- Instructor Consent:
No consent required