2019/20 Undergraduate Module Catalogue
MATH3823 Generalised Linear Models
10 creditsClass Size: 63
Module manager: Dr Benjamin Thorpe
Taught: Semester 2 View Timetable
Year running 2019/20
Pre-requisite qualificationsMATH2735 or MATH2715
This module is mutually exclusive with
|MATH5824M||Generalised Linear and Additive Models|
This module is approved as a discovery module
Module summaryLinear regression is a tremendously useful statistical technique but is very limited. Generalised linear models extend linear regression in many ways - allowing us to analyse more complex data sets. In this module we will see how to combine continuous and categorical predictors, analyse binomial response data and model count data.
ObjectivesOn completion of this module, students should be able to:
a) carry out regression analysis with generalised linear models including the use of link functions;
b) understand the use of deviance in model selection;
c) appreciate the problems caused by overdispersion;
d) fit and interpret the special cases of log linear models and logistic regression;
e) use a statistical package with real data to fit these models to data and to write a report giving and interpreting the results.
Generalised linear model; probit model; logistic regression; log linear models.
|Delivery type||Number||Length hours||Student hours|
|Private study hours||76.00|
|Total Contact hours||24.00|
|Total hours (100hr per 10 credits)||100.00|
Private studyStudying and revising of course material.
Completing of assignments and assessments.
Opportunities for Formative FeedbackRegular example sheets.
Methods of assessment
|Assessment type||Notes||% of formal assessment|
|Total percentage (Assessment Coursework)||20.00|
There is no resit available for the coursework component of this module. If the module is failed, the coursework mark will be carried forward and added to the resit exam mark with the same weighting as listed above.
|Exam type||Exam duration||% of formal assessment|
|Standard exam (closed essays, MCQs etc)||2 hr 00 mins||80.00|
|Total percentage (Assessment Exams)||80.00|
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading listThe reading list is available from the Library website
Last updated: 30/09/2019
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