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STATS 270. Bayesian Statistics I. 3 Units.

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.
Same as: STATS 370

School of Engineering

http://exploredegrees.stanford.edu/schoolofengineering/

...be taken rather than STATS 110 Statistical Methods...267 , CS 269I, CS 270 , CS 272 , CS...