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MA50260: Statistical modelling

[Page last updated: 15 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: Department of Mathematical Sciences
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 2
Further information on unit assessment Assessment Summary: EX 100%
Further information on unit assessment Assessment Detail:
  • Examination (EX 100%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites 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.
Further information on programme availabilityProgramme availability:

MA50260 is Compulsory on the following programmes:

Department of Computer Science