Bayesian Statistics (975C8)
Bayesian Statistics
Module 975C8
Module details for 2025/26.
15 credits
FHEQ Level 7 (Masters)
Module Outline
This module builds on the Autumn semester module Research Reform and Open Science and further explores Bayesian approaches to statistics, including analysis of data. Bayesian approaches are especially well suited to modelling real-world problems, and this will be reflected in both the examples covered in the workshops and in the topics for the assessments. Bayesian approaches will be compared to frequentists approaches and the strengths and weaknesses of both approaches will be discussed.
Full Module Description
This module builds on the Autumn semester module Research Reform and Open Science and further explores Bayesian approaches to statistics, including analysis of data. Bayesian approaches are especially well suited to modelling real-world problems, and this will be reflected in both the examples covered in the workshops and in the topics for the assessments. Bayesian approaches will be compared to frequentists approaches and the strengths and weaknesses of both approaches will be discussed.
Module learning outcomes
Understand various types of probability distributions
Perform a summary of distributions, involving for instance credible intervals and indices of effect "significance" simple hierarchical models.
Evaluate and understand Bayesian models
Interpret Bayesian results by reporting and visualizing Bayesian models
| Type | Timing | Weighting | 
|---|---|---|
| Take Away paper (2000 words) | Spring Semester Week 5 Wed 16:00 | 45.00% | 
| Take Away paper (2000 words) | Spring Semester Week 11 Wed 16:00 | 55.00% | 
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern | 
|---|---|---|---|
| Spring Semester | Workshop | 2 hours | 11111111111 | 
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Dominique Makowski
Assess convenor, Convenor
/profiles/592424
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