Handbook

This subject explores the use of statistical techniques to answer questions posed by researchers. It starts by determining the types of data to be collected and how this should be done to maximise the information obtained. It then considers various methods of statistical data analysis that might be required and considers their underlying assumptions, the situations in which they may be appropriate and what results can be obtained. Emphasis will be placed on interpreting these results, communicating with colleagues and using a statistical package. The methods of design and analysis will be illustrated by case studies. The learning will be motivated by applying the subject material to a practical experiment.

• Brief introduction or revision of t-tests, one-way Analysis of Variance (ANOVA) and use of a statistical package.
• Design and analysis of factorial designs, split-plot designs and repeated measures designs.
• Generalised linear models, including logistic regression and Poisson (or `log-linear') regression.
• Multivariate techniques, including multivariate graphical techniques and multivariate ANOVA.
• Project planning.