MAS6002   Statistical Laboratory   (20 credits)

Description

The unit will introduce students to a range of statistical techniques and give practice in their implementation and interpretation using modern software. It aims to help students develop the knowledge and experience to select and use appropriate statistical techniques for a variety of problems. The emphasis will be on practical application of techniques and knowledge of their scope rather than development of theoretical underpinnings (which will be met in other units). Areas to be covered include: exploratory data analysis, simple checks on data, non-parametric methods (including density estimation), linear and generalised linear modelling, time series, multivariate analysis and display and some of tree-based methods, robust methods, local regression methods, spatial data analysis, non-linear regression techniques and generalised additive modelling. The main software used will be S-PLUS and R; SAS will also be used.

Reading List