Bayesian methods
Supervisor: Paul Fahey
Description: This course covers: how we conceptualise probability (the Frequentist/Bayesian debate); the Bayesian framework; defining prior distributions; updating prior distributions with data to obtain posterior distributions; hierarchical models; model checking and sensitivity analysis; regression models; maximum likelihood methods; simulation methods (including Markov Chain Monte Carlo).
Prerequisites: STA3301 Statistical Models (and all of it's pre-requisites)
Main text: Either Gelman A, 2003. Bayesian Data Analysis (2nd ed). Chapman & Hall/CRC. Boca Raton. Or Gill J, 2002. Bayesian Methods: A Social and Behavioural Sciences Approach. Chapman & Hall/CRC. Boca Raton.
Some potential study topics
| What is Maths? Ron Addie | Attitude and belief Patricia Cretchley | Computer Algebra Ed Patricia Cretchley | Assessment issues Patricia Cretchley |
| Education research? Patricia Cretchley | Bridge gaps Patricia Cretchley | Gender equity Patricia Cretchley | Teaching geometry Patricia Cretchley |
| Math history Patricia Cretchley | Gen Lin Models Peter Dunn | Bayesian stats Paul Fahey | Survey sampling Ashley Plank |
| Maths Methods Tony Roberts | Quantum Computing Tony Roberts | Water waves Tony Roberts | Games theory Tony Roberts |
| Parallel numerics Tony Roberts | Hydro stability Sergey Suslov | Math Biology Sergey Suslov | Banach spaces Oleksiy Yevdokimov |
| Fundamental Maths Education Oleksiy Yevdokimov | Number history Oleksiy Yevdokimov |