MATH6025 Bayesian Methods
Module Overview
This module will consolidate the basic concepts of Bayesian inference covered in Statistical Theory or MATH3044 Statistical Inference. Students will be introduced to more advanced Bayesian methodology, and to the analysis of data using Bayesian methods.
Aims and Objectives
Module Aims
This module will consolidate the basic concepts of Bayesian inference covered in Statistical Theory or MATH3044 Statistical Inference. Students will be introduced to more advanced Bayesian methodology, and to the analysis of data using Bayesian methods.
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Appreciate the motivation for using Bayesian inference
- Make appropriate inferences within a Bayesian framework
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Apply numerical methods for making inferences in more complex problems within a suitable statistical software package
Syllabus
• Motivation behind Bayesian inference; connections with the classical approach • Revision of Prior and posterior distributions • Estimation and loss functions • Prior distribution choice, conjugate priors and non-informative priors • Prediction • Hypothesis testing, Bayes Factor, and Bayesian model averaging • Bayesian computation with Markov Chain Monte Carlo • Implementing Bayesian methods using a suitable Bayesian modelling software package
Special Features
Students must attend the Co-requisite module Math6153 in the autumn.
Learning and Teaching
Teaching and learning methods
12 hours of lectures and 4 hours of practical laboratory sessions within the first six weeks.
| Type | Hours |
|---|---|
| Lecture | 12 |
| Independent Study | 36 |
| Specialist Laboratory | 4 |
| Total study time | 52 |
Assessment
Summative
| Method | Percentage contribution |
|---|---|
| Coursework () | 30% |
| Project | 70% |
Referral
| Method | Percentage contribution |
|---|---|
| Project report () | 100% |
Repeat Information
Repeat type: Internal & External
Linked modules
Co-requisites
To study this module, you will need to also study the following module(s):
| Code | Module |
|---|---|
| MATH6153 | Statistical Theory and Linear Models |
Costs
Costs associated with this module
Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.
In addition to this, students registered for this module typically also have to pay for:
Books and Stationery equipment
Course texts are provided by the library and there are no additional compulsory costs associated with the module.
Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at www.calendar.soton.ac.uk.