Module Identifier MA37510  
Academic Year 2001/2002  
Co-ordinator Mr David Jones  
Semester Semester 2  
Pre-Requisite MA36510  
Course delivery Lecture   19 x 1 hour lectures  
  Seminars / Tutorials   3 x 1 hour example classes  
Assessment Exam   2 Hours (written examination)   100%  
  Resit assessment   2 Hours (written examination)   100%  

General description

This module builds on the work in MA36510 by focusing on some of the many and varied applications of the Linear Model and considers techniques and modifications that have been motivated by them. Modern developments in the area are also considered.


To make the student aware of some of the applications of Linear Models and to consider new developments.

Learning outcomes

On completion of this module, a student should be able to:


1. EXTENSIONS OF THE LINEAR MODEL: Correlated and/or heteroscedastic observations. The Generalized Gauss Markov Theorem. Non-invertible designs. One and two-way models.
2. COMPARISON OF MODELS: Orthogonality. Orthogonal polynomials. Weighing designs. Brief treatment of design optimality.
3. GENERALIZED LINEAR MODELS: Basic ideas. The exponential family. Link functions and canonical links. Deviance. Examples including models for exponential, binomial and Poisson data.
4. DIAGNOSTICS: Ordinary, standardized and studentized residuals. Leverages. Deletion statistics.

Reading Lists

** Recommended Text
R H Myers and J S Milton. (1991) A first course in the theory of linear statistical models. PWS-Kent 0534916457
** Supplementary Text
F A Graybill. (1976) Theory and application of the linear models. Duxbury 0878721088