ST300      Half Unit
Regression and Generalised Linear Models

This information is for the 2018/19 session.

Teacher responsible

Dr Xinghao Qiao


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


Students must have completed:

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

AND Elementary Statistical Theory (ST102).

Course content

A solid coverage of the most important parts of the theory and application of regression models, generalised linear models and the analysis of variance. Analysis of variance models; factors, interactions, confounding. 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 a statistics package will be an integral part of the course. The computer workshops revise the theory and show how it can be applied to real datasets.


10 hours of lectures and 9 hours of classes in the MT. 10 hours of lectures and 9 hours of classes in the LT. 1 hour of lectures in the ST.

Week 6 reading week in MT will be for revision of taught materials, while week 6 reading week in LT will be for your project completion. 

Indicative reading

D C Montgomery, E A Peck & G G Vining, Introduction to Linear Regression Analysis; D C Montgomery, Design and Analysis of Experiments; A J Dobson, An Introduction to Generalised Linear Models; P McCullagh & J A Nelder, Generalized Linear Models; A C Atkinson, Plots, Transformations and Regression; A C Atkinson & M Riani, Robust Diagnostic Regression Analysis; JJ Faraway, Linear Models with R; JJ Faraway, Extending the linear Model with R. Related items from the Institute of Actuaries, Core reading Subject CT6. For full details of the syllabus of CT6, see


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

Student performance results

(2015/16 - 2017/18 combined)

Classification % of students
First 38.9
2:1 16
2:2 21.1
Third 17.1
Fail 6.9

Key facts

Department: Statistics

Total students 2017/18: 65

Average class size 2017/18: 17

Capped 2017/18: No

Lecture capture used 2017/18: Yes (MT & LT)

Value: Half Unit

Guidelines for interpreting course guide information

PDAM skills

  • Problem solving
  • Application of numeracy skills