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Informatics and Computing
Term : Summer 2024
Catalog Year : 2023-2024

INF 626 - Applied Bayesian Modeling

Description: Bayesian statistical methods for analyzing data, with emphasis on ecological and biological data. Includes Bayes rule, basic Bayesian formulation (priors, posteriors, likelihoods), single- and multiple-parameter models, hierarchical models, generalized linear models, multivariate models, mixture models, models for missing data, merging statistical and process models, overview of spatial and temporal processes, and introduction to computation methods. Letter grade only.

Units: 3

Sections offered: Fall 2024

Prerequisite: Graduate Status