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BST 228 - Applied Bayesian Analysis or return to Course Catalog Search

203515 – Section 1   

SchoolDepartmentFaculty
Harvard T.H. Chan School of Public HealthBiostatisticsCorwin Zigler
TermDay and TimeLocation
Fall (Full Semester) 2017  (show academic calendar)TuTh   9:45 a.m. - 11:15 a.m.Kresge 200 (HSPH)
Credits
5  (show credit conversion for other schools)
Credit Level
Graduate

Description
This course is a practical introduction to the Bayesian analysis of biomedical data. It is anintermediate Master's level course in the philosophy, analytic strategies, implementation, and interpretation of Bayesian data analysis. Specific topics that will be covered include: the Bayesian paradigm; Bayesian analysis of basic models; Bayesian computing: Markov Chain Monte Carlo; STAN R software package for Bayesian data analysis; linear regression; hierarchical regression models; generalized linear models; meta-analysis; models for missing data.Programming and case studies will be used throughout the course to provide hands-on training in these concepts.Prerequisites: BST210 and BST222, or permission of the instructor

Prerequisite(s)
HSPH: BST228

 
Cross Registration
Eligible for cross-registration
With permission of instructor/subject to availability

MIT students please cross register from MIT's Add/Drop application.

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