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MA50260: Statistical modelling

[Page last updated: 05 August 2021]

Academic Year: 2021/2
Owning Department/School: Department of Mathematical Sciences
Credits: 6 [equivalent to 12 CATS credits]
Notional Study Hours: 120
Level: Masters UG & PG (FHEQ level 7)
Semester 2
Assessment Summary: EX 100%
Assessment Detail:
  • Examination (EX 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: Before taking this module you must take XX50215
Description: Aims:
To understand and apply linear, generalised linear and mixed effect models (GLMM).

Learning Outcomes:

* choose an appropriate generalised linear mixed model for a given set of data;
* fit this model, select terms for inclusion in the model and assess the adequacy of a selected model;
* make inferences on the basis of a fitted model and recognise the assumptions underlying these inferences and possible limitations to their accuracy.

Problem solving (T, F, A), computing (T, F, A), written communication (F, A).

Multiple linear regression: inference techniques for the general linear model, diagnostics, transformation and variable selection. Generalised linear models: exponential family of distributions and inference procedures. Logistic regression and log-linear models. Mixed effect models: hierarchical and grouped data, nested and crossed designs.

Programme availability:

MA50260 is Compulsory on the following programmes:

Department of Computer Science Department of Mathematical Sciences
  • TSMA-AFM19 : MSc Mathematics with Data Science for Industry
  • TSMA-AWM19 : MSc Mathematics with Data Science for Industry


  • This unit catalogue is applicable for the 2021/22 academic year only. Students continuing their studies into 2022/23 and beyond should not assume that this unit will be available in future years in the format displayed here for 2021/22.
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