3.00 Credits
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-parapmeter models, hierarchicial models, generalized linear models, multivariate models, misture models, models for missing data, merging statisical and process models, and introduction to computation methods. Cross listed with STAT/ECOL 5380. Prerequisites: at least 2 semesters of calculus and one semester of statistics.