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MT5753 STATISTICAL MODELLING
Compulsory module for M. Res. Environmental Biology and M. Res. in Environmental Biology Conversion for Mathematical, Physical and Molecular Sciences Postgraduate Taught Programmes.
AimsThis course teaches linear and generalized linear models using a data-based approach. A case-study is used throughout the course and each chapter begins with research questions which are addressed using the methods contained inside.
ObjectivesBy the end of the course students are expected to be able to use generalized linear models to help understand research questions, to understand the assumptions of the methods and to be able to interpret and criticise analysis results.
SyllabusThe following methods/issues are covered:
This course aims to teach good statistical modelling practice in addition to model details, and so exploratory data analysis, model specification & fitting and model assessment issues are covered for each data type.
TextbooksAn R and S-PLUS Companion to Applied Regression by John Fox (2002)
Extending the linear model with R: generalized linear, mixed effects, and nonparametric regression models by Julian Faraway (2006): Chapman and Hall/CRC Press
Course materials and software
Course notes with gaps will be provided. All examples in the course notes will be performed using R and SAS software and all code required in the course (and practicals) will be provided, so no previous experience with these software packages is assumed.
AssessmentTwo hour examination: 50% Continuous assessment: 50%
PrerequisitesAt least one MT4000 level module
AvailabilityEvery year in semester 1 at 2 (4 weeks: time provisional)
LecturersDr M L MacKenzie, Ms L Scott-Hayward
Click here for access to past examination papers via iSaint.
Click here to see the University Course Catalogue entry.
Revised: PMH (September 2012)