STATS 451 - Bayesian Data Analysis
Section: 001
Term: WN 2018
Subject: Statistics (STATS)
Department: LSA Statistics
Credits:
3
Requirements & Distribution:
BS
Waitlist Capacity:
99
Advisory Prerequisites:
(STATS 426 or STATS 412) and (STATS 306 or STATS 406).
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May not be repeated for credit.

The course is an introduction to both the principles and practice of Bayesian inference for data analysis. At the end of this course students will be familiar with the Bayesian paradigm, and will be able to analyze different classes of statistical models. The course gives an introduction to the computational tools needed for Bayesian data analysis and develops statistical modeling skills through a hands-on data analysis approach. Topics include: prior/posterior distributions, Bayes rule, Markov Chain Monte Carlo computations, linear and generalized linear models, mixed effect models, hierarchical models, analysis of spatial data, model selection and comparison, model checking.

STATS 451 - Bayesian Data Analysis
Schedule Listing
001 (LEC)
P
32535
Open
59
59STATS Maj
-
MW 1:00PM - 2:30PM
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