## STATS 270: Bayesian Statistics I (STATS 370)

This is the first of a two course sequence on modern Bayesian statistics. Topics covered include: real world examples of large scale Bayesian analysis; basic tools (models, conjugate priors and their mixtures); Bayesian estimates, tests and credible intervals; foundations (axioms, exchangeability, likelihood principle); Bayesian computations (Gibbs sampler, data augmentation, etc.); prior specification. Prerequisites: statistics and probability at the level of
Stats300A,
Stats305, and
Stats310.

Terms: Win
| Units: 3

Instructors:
Diaconis, P. (PI)
;
Sabatti, C. (PI)
;
Wong, W. (PI)
...
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