MA50260: Statistical modelling
[Page last updated: 15 October 2020]
Academic Year: | 2020/1 |
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) |
Period: |
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Assessment Summary: | EX 100% |
Assessment Detail: |
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Supplementary Assessment: |
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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. 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
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Notes:
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