modules

Statistical modelling lies at the heart of modern data analysis and is a vital part of data science. Simple statistical models include the techniques of regression and multiple regression familiar from most foundation courses in statistics. This module takes those ideas further placing them in the much broader context of the Generalized Linear Model. It then goes on to consider extensions to that framework involving random effects, Generalized Linear Mixed Models, Generalized Additive Models but also models for failure time data with partially observed information. We will use the statistical software R as the main platform to fit this wide range of models, and will use it in practical sessions so that, as well as a sound theoretical basis, you will develop an understanding of how to apply techniques discussed in the course in practical data analysis.

Pre-requisite Module: MTH2006 Statistical Modelling & Inference, or equivalent

_{Please note that all modules are subject to change, please get in touch if you have any questions about this module.}