General description
This module covers the theory of some of the most commonly used statistical techniques - regression and the analysis of variance. It also includes practical application of these important techniques.

Aims
This module will provide a thorough grounding in the basic theory associated with some important statistical models.

Learning outcomes
On completion of this module, a student should be able to:

• explain the theory of statistical regression and, in particular, the general principle of least squares;
• explain the rationale behind, and the underlying theory of, the analysis of variance;
• carry out appropriate analyses and draw conclusions.

Syllabus
1. SIMPLE LINEAR REGRESSION: Theory of least squares. Normal equations. Sampling distribution of estimators. Confidence intervals and tests. Prediction. Correlation. Residuals.
2. EXTENSIONS: Transformation to linear relationship. Extension of the basic ideas to regression on two independent variables.
3. THE ANALYSIS OF VARIANCE: One way and two way classification. Interaction. Checking assumptions. Interpretation of analyses. Contrasts.