ST300      Half Unit
Regression and Generalised Linear Models

This information is for the 2022/23 session.

Teacher responsible

Dr Philip Chan


This course is available on the BSc in Actuarial Science, BSc in Business Mathematics and Statistics, BSc in Data Science, BSc in Financial Mathematics and Statistics, BSc in Mathematics with Economics and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.

This course is not capped, any student that requests a place will be given one


Students must have completed:

EITHER Probability, Distribution Theory and Inference (ST202) OR Probability and Distribution Theory (ST206)

AND Mathematical Methods (MA100) or equivalent.

It is assumed students have taken at least a first course in linear algebra.

Previous programming experience is not required  but students who have no previous experience in R must complete an online pre-sessional R course from the Digital Skills Lab before the start of the course (

Course content

A solid coverage of the most important parts of the theory and application of regression models, and generalised linear models. Multiple regression and regression diagnostics. Generalised linear models; the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, deviance residuals. Model choice, fitting and validation.

The use of the statistics package RStudio will be an integral part of the course. The computer workshops revise the theory and show how it can be applied to real datasets.


This course will be delivered through a combination of lectures and classes totalling a minimum of 30 hours in Michaelmas Term.

This course includes a reading week in Week 6 of Lent Term.

Indicative reading

Dobson, A.J. (2008). An Introduction to Generalized Linear Models.

Fox, J. (2015). Applied Regression Analysis and Generalized Linear Models

Frees, E.W. (2010). Regression Modeling with Actuarial and Financial Applications



Exam (85%, duration: 2 hours) in the summer exam period.
Project (15%) in the LT.

Student performance results

(2019/20 - 2021/22 combined)

Classification % of students
First 33.2
2:1 42.5
2:2 16.8
Third 4.1
Fail 3.4

Key facts

Department: Statistics

Total students 2021/22: 94

Average class size 2021/22: 23

Capped 2021/22: No

Value: Half Unit

Guidelines for interpreting course guide information

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Personal development skills

  • Problem solving
  • Application of numeracy skills
  • Specialist skills