Applied Statistical Modelling

Module code: MTH7021P

Credits: 15.0
Semester: SEM1

Contact: Dr Adrian Baule

The module aims to provide students with a solid understanding of the theory and applications of the General Linear Models as used in modern Statistical Applications. This framework of models consists of a generalisation of linear regression that includes more general response variables such as binary, multinomial, ordinal, Poisson random variables amongst others where the underlying parameters or a function of them depend in linear fashion of the input variables.
The module will provide an introduction to the basic techniques in these advanced topics. Including a review of linear and logistic regression and will progress onto how this model can be extended to more general random variables.

Connected course(s): UDF DATA
Assessment: 80.0% Examination, 20.0% Coursework
Level: 7