BAY is delivered in alternate (even) years.
Prof Lyle Gurrin, Melbourne School of Population & Global Health, University of Melbourne
Epidemiology, Mathematical Background for Biostatistics, Probability and Distribution Theory, Principles of Statistical Inference, Linear Models, Categorical Data and Generalised Linear Models
8-12 hours total study time per week
Semester 2 in year of delivery (offered in even years)
Assignments 60% (two major assignments worth 30% each) and submission of selected practical exercises 40%
Gelman A, Carlin JB, Stern HS, Rubin DB, Dunson DB, Vehtari A Bayesian Data Analysis, 3rd edition. Chapman and Hall 2013 For details, including ISBN, see the BCA Textbook and Software Guide
Microsoft Excel, Stata or R for simple calculations. R for simulations and model fitting using MCMC routines
Topics include simple one-parameter models with conjugate prior distributions; standard models containing two or more parameters, including specifics for the normal location-scale model; the role of noninformative prior distributions; the relationship between Bayesian methods and standard “classical” approaches to statistics, especially those based on likelihood methods; computational techniques for use in Bayesian analysis, especially the use of simulation from posterior distributions, with emphasis on the WinBUGS package as a practical tool; application of Bayesian methods for fitting hierarchical models to complex data structures.
Course notes, assignment material and interaction facilities available online