好色tv

- Academic Registry


MA40189: Topics in Bayesian statistics

[Page last updated: 22 May 2025]

Academic Year: 2025/26
Owning Department/School: Department of Mathematical Sciences
Credits: 6 [equivalent to 12 CATS credits]
Notional Study Hours: 120
Level: Masters UG & PG (FHEQ level 7)
Period:
Semester 2
Assessment Summary: EXCB 100%
Assessment Detail:
  • Examination (EXCB 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: Before taking this module you must take MA40092
Learning Outcomes: : Students should be able to formulate the Bayesian treatment and analysis of many familiar statistical problems.


Synopsis: You will learn the theory of Bayesian inference and apply Bayesian methods to a variety of statistical models and data types.

Content: The Bayesian method: Bayes theorem, using Bayes theorem for parametric inference, sequential updating, conjugacy, using the posterior for inference, interval summaries. Modelling: predictive distribution, exchangeability, de Finetti's Representation Theorem, sufficient statistics, conjugacy and exponential families, prior specification including default prior selection methods such as the Jeffreys prior. Computation: normal approximations, Monte Carlo integration, importance sampling, basic idea of Markov chain Monte Carlo, Metropolis-Hastings algorithm, Gibbs sampling.

Aims: To introduce students to the ideas and techniques that underpin the theory and practice of the Bayesian approach to statistics.

Course availability:

MA40189 is Optional on the following courses:

Department of Mathematical Sciences
  • USMA-AFM14 : MMath(Hons) Mathematics (Year 4)
  • USMA-AAM15 : MMath(Hons) Mathematics with Study year abroad (Year 4)
  • USMA-AKM15 : MMath(Hons) Mathematics with Year long work placement (Year 5)

Notes:

  • This unit catalogue is applicable for the 2025/26 academic year only. Students continuing their studies into 2026/27 and beyond should not assume that this unit will be available in future years in the format displayed here for 2025/26.
  • 好色tv and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.