MAS6011   Dependent Data   (20 credits)

Description

The unit develops concepts and techniques for the analysis of data having the complex structure typical of many real applications. The two main themes are the analysis of observations on several dependent variables, and the analysis of dependent observations made over a period of time on a single variable. The unit begins with a practical introduction to multivariate analysis: Data Mining techniques such as summarising and displaying high dimensional data and dimensionality reduction principal components, multidimensional scaling, multivariate analysis of variance and discrimination. A review of repeated measures problems links to ideas of time series analysis. General techniques for the study of time series are developed, including structural descriptions, Box-Jenkins and state-space models and their fitting, techniques for forecasting and an introduction to spectral methods. Emphasis is given to the practical implementation of the techniques using appropriate computer packages.

Reading List