Mathematics

Linear Statistical Models

Module code: G1107
Level 6
15 credits in autumn teaching
Teaching method: Lecture, Practical
Assessment modes: Coursework, Unseen examination

Topics include:

  • full-rank model (multiple and polynomial regression), estimation of parameters, analysis of variance and covariance
  • model checking
  • comparing models, model selection
  • transformation of response and regressor variables
  • models of less than full rank (experimental design), analysis of variance, hypothesis testing, contrasts
  • simple examples of experimental designs, introduction to factorial experiments
  • use of a computer statistical package to analyse real data sets.

Module learning outcomes

  • Understand the theory of the general linear model and derive distributional results relating to estimators.
  • Apply the general linear model of full rank to a variety of applications, using transformations and variable selection techniques.
  • Understand the benefits of designed experiments, select and carry out statistical analyses and report conclusions clearly.
  • Use SAS to fit regression and analysis of variance models, compute additional statistics and construct diagrams.