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MA50260: Statistical modelling

[Page last updated: 03 August 2022]

Academic Year: 2022/23
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
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.

Aims: To understand and apply linear, generalised linear and mixed effect models (GLMM).

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

Content: 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 2022/23 academic year only. Students continuing their studies into 2023/24 and beyond should not assume that this unit will be available in future years in the format displayed here for 2022/23.
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