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MAS8405 : Bayesian Data Analysis (Inactive)

  • Inactive for Year: 2024/25
  • Module Leader(s): Professor Chris Oates
  • Owning School: Mathematics, Statistics and Physics
  • Teaching Location: Newcastle City Campus

Your programme is made up of credits, the total differs on programme to programme.

Semester 2 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System


Bayesian analysis provides a principled approach for the synthesis of information from different sources. These principles have been adopted across a wide variety of areas within science, industry, machine learning, and AI. This has been made possible by the development of powerful computational algorithms for Bayesian analysis. This module starts with an introduction to the principles of Bayesian analysis before moving on to more complex models and computational algorithms relevant to practical data analysis.

Specifically, the module aims to equip students with the following knowledge and skills:

To gain an understanding of the principles and the practical applications of the Bayesian approach to data analysis.

To gain knowledge of modern computational methods for Bayesian analysis and their application to real-world problems.

Outline Of Syllabus

Principles of Bayesian inference

Conjugate priors

Computational methods, such as Markov chain Monte Carlo (MCMC)

Applications, such as: linear models, generalized linear models, mixture models, hidden Markov models, dynamic linear models, Gaussian process regression

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion114:0014:00Formative report
Structured Guided LearningLecture materials62:0012:00Present in person lectures, which are also recorded and made available via Recap
Scheduled Learning And Teaching ActivitiesPractical62:0012:00Present in person practical
Guided Independent StudyProject work132:0032:00Main project
Scheduled Learning And Teaching ActivitiesDrop-in/surgery62:0012:00present in person drop-in
Guided Independent StudyIndependent study63:0018:00Lecture follow-up/background reading
Teaching Rationale And Relationship

Lectures are used for the delivery of theory and explanation of methods, illustrated with examples. Practicals are used both for solution of problems and to give insight into the ideas/methods studied. There are present-in-person practical sessions and present-in-person drop-in sessions each week to ensure rapid feedback on understanding.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report2M100A compulsory report allowing students to demonstrate skills and knowledge gained during the course.
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Practical/lab report2MA compulsory report allowing students to develop problem solving techniques & to practise the methods learnt and to assess progress
Assessment Rationale And Relationship

A compulsory formative practical report allows the students to develop their problem-solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback, before the summative assessments.

Reading Lists