STATS 331 - Introduction to Bayesian Statistics
Faculty
Science
Department
Statistics
Points:
15
Available Semesters:
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Course Components
Labs
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Lectures
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Description: Introduces Bayesian data analysis using the WinBUGS software package and R. Topics include the Bayesian paradigm, hypothesis testing, point and interval estimates, graphical models, simulation and Bayesian inference, diagnosing MCMC, model checking and selection, ANOVA, regression, GLMs, hierarchical models and time series. Classical and Bayesian methods and interpretations are compared.
Prerequisites / Restrictions
Prerequisite: ENGSCI 314 or STATS 201 or 208
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