ST300      Half Unit
Regression and Generalised Linear Models

This information is for the 2025/26 session.

Course Convenor

Dr Mona Azadkia

Availability

This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Financial Mathematics and Statistics, BSc in Mathematics with Economics, BSc in Mathematics, Statistics and Business, Erasmus Reciprocal Programme of Study and Exchange Programme for Students from University of California, Berkeley. This course is freely available as an outside option to students on other programmes where regulations permit. It does not require permission. This course is freely available to General Course students. It does not require permission.

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

Requisites

Pre-requisites:

Students must have completed MA100 and ST202 before taking this course.

Additional requisites:

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

(https://moodle.lse.ac.uk/course/view.php?id=8714)

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.

Teaching

20 hours of lectures and 10 hours of classes in the Winter Term.

This course has a reading week in Week 6 of Winter 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

Assessment

Exam (80%), duration: 120 Minutes in the Spring exam period

Continuous assessment (20%)


Key facts

Department: Statistics

Course Study Period: Winter Term

Unit value: Half unit

FHEQ Level: Level 6

CEFR Level: Null

Total students 2024/25: 49

Average class size 2024/25: 16

Capped 2024/25: No
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