Generalised Linear Models (Level M) STATS5019

  • Academic Session: 2018-19
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes

Short Description

This course introduces the class of models known as generalised linear models, providing an overview of the theory of estimation and inference as well as practical examples from various areas of applications.

Timetable

20 lectures (2 each week in Weeks 1-10 of Semester 2), 5 tutorials (fortnightly), two 2-hour practical classes.

Requirements of Entry

None

Excluded Courses

STATS4043 Generalised Linear Models

STATS3TBC Statistics 3G: Generalised Linear Models

Assessment

120-minute, end-of-course examination

Main Assessment In: April/May

Course Aims

To provide an overview of linear statistical models and their generalizations;

To acquaint students with the theory of generalized linear models;

To provide practical examples from various areas of applications.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ use models with various link functions and link distributions such as models for discrete data;

■ perform binary regression and analysis of contingency tables;

■ apply log-linear models;

■ analyse a given set of data using generalised linear models;

■ explain and rigorously derive key aspects of the theory of generalised linear models.

Minimum Requirement for Award of Credits

None