Generalised Linear Models

Module code: MA3201

This module extends the ideas used in Linear Statistical Models to a more general framework, which allows the possibility of including a number of analyses in one general approach. This occurs in the case when the response variable is dependent through some link function on a predictor of an unknown linear combination of the explanatory variables as well as an error random variable. With a suitable choice of link function and error structure it is possible to cover, within a general framework, a number of techniques for analysing data, such as linear modelling of continuous variables, log-linear modelling for the analysis of counts and proportions, linear logistic regression modelling for binary data, Poisson regression. Two prime objectives of an analysis using these models include a determination of which explanatory variables are important, and exactly how these variables are related to the response variable. We will use statistical software to analyse data using these models.

Learning

  • 33 hours of lectures
  • 2 hours of seminars
  • 11 hours of practical classes and workshops
  • 104 hours of guided independent study

Assessment

  • Exam, 2 hours (70%)
  • Coursework (30%)