MX37210 - REGRESSION AND ANOVA

Module Identifier	MX37210
Module Title	REGRESSION AND ANOVA
Academic Year	2001/2002
Co-ordinator	Mr David Jones
Semester	Semester 2
Other staff	Dr J Basterfield
Pre-Requisite	MX36010
Mutually Exclusive	MA27210
Course delivery	Lecture	14 x 1 hour lectures
	Seminars / Tutorials	2 x 1 hour example classes
	Practical	6 x 2 hour practical classes
Assessment	Course work		20%
	Exam	2 Hours (written examination)	80%
	Resit assessment	2 Hours (written examination)	100%

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 rationale behind, and the underlying theory of, the analysis of variance;
explain the issues that arise in extending regression from one predictor variable to two;
carry out appropriate analyses and draw conclusions.

Syllabus

1. THE ANALYSIS OF VARIANCE: One way and two way classification. Models. Estimators, confidence intervals and tests. Residuals and fitted values. Checking assumptions. Interpretation of analyses. Contrasts. Interactions. Transformation of data.
2. BIVARIATE REGRESSION: Least Squares estimators. Comparison with one predictor. Interpretation of sequential sums of squares. Standardised residuals.

Reading Lists

Books
** Supplementary Text
F Daly, D J Hand, M C Jones, A D Lunn & K J McConway. (1995) Elements of Statistics. Addison-Wesley 0201422786
W Mendenhall, D D Wackerly & R L scheaffer. (1996) Mathematical Statistics with Applications. 5th. PWS-Kent 0534209165