Statistics 3G: Generalised Linear Models STATS3014

  • Academic Session: 2019-20
  • School: School of Mathematics and Statistics
  • Credits: 10
  • Level: Level 3 (SCQF level 9)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes

Short Description

This course provides an introductory overview of 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

The normal requirement is that students should have been admitted to the third year of the Designated Degree programme in Statistics.

Excluded Courses

Generalised Linear Models [STATS 4043]

Generalised Linear Models (Level M) [STATS5019]

Co-requisites

The courses prescribed in the Designated Degree programme to which the student has been admitted.

Assessment

90-minute, end-of-course examination (100%)

Main Assessment In: April/May

Course Aims

The aims of this course are:

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

■ 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 simple data sets using generalised linear models.

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.