ST404-15 Applied Statistical Modelling

Introductory description

This module runs in Term 2 and is core for students on MMORSE or MMathStat courses (Integrated Masters).
It is not available as an Unusual Option to any other students.

Pre-requisites: ST218, ST219 and ST221

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

• Modelling strategies for multiple regression on real data
• Diagnostic analysis for statistical linear models using R
• Extensions to the classic linear statistical model
• Generalised linear models
• Teamwork, leadership & communication
• Oral presentation and academic writing skills

Learning outcomes

By the end of the module, students should be able to:

• Be able to build, interpret and evaluate a statistical model for a real data set;
• Have gained experience of working in a team on a statistical investigation;
• Have practised their oral and written presentation skills.

Indicative reading list

S. Sheather (2009). A modern approach to regression with R. Springer Science & Business Media.
J. Derr (2000). Statistical consulting: A guide to effective communication.
J Faraway (2002): Practical Regression and ANOVA using R.
J. Fox and S.Weisberg (2002): An R Companion to Applied Regression. Springer.

View reading list on Talis Aspire

Subject specific skills

Exploratory data analysis, practical data modeling, the use of data transformations. Application of generalized linear models, model criticism: residual and influential analysis, multicollinearity, variable selection including Bayesian and shrinkage methods. Use of statistical software.

Transferable skills

Report writing and presentation skills. Team working. Use of code in programs. Critical thinking and problem solving. Self-reflection . Team management.