BIOS574B
Download as PDF
BIOS574B - Bayesian Statistical Theory and Applications
Course ID
012959
Course Description
Basic theory of Bayesian inference, including analytical and numerical methods for assessing posterior and predictive distributions, and applications. Topics will include Bayesian analysis of normal linear regression and computational methods including Markov chain Monte Carlo.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Graduate
Course Attributes
CE - CL (Cross Listed), GIDP - GC (Global Change), GIDP - STATD (Statistics and Data Science)
Course Requisites
ECON 522A, ECON 522B; concurrent registration, MATH/STAT 566 and MATH/STAT 571A.
Cross Listed Courses
May be convened with
Component
Lecture
Optional Component
No