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LINEAR MODELS (R)

Module code: ST833
Credits: 5
Semester: 1
Quota: Restricted entry, contact department for details before registering
Department: MATHEMATICS AND STATISTICS
International:

	Overview
	Overview -------- Scatterplots and regression. The multiple regression model and its applications. Matrix notation, mean vectors and covariance matrices. Least-squares estimation. The multivariate normal distribution. Hypothesis testing and confidence intervals, prediction. Simple linear regression as a special case. Analysis of variance, R2, sequential sums of squares, general F-tests. Added variable plots. Model checking via testing for lack of fit and residual plots. Regression diagnostics: residuals, leverage, outliers, influence and Cook's Distance. Polynomials and factors in regression. Weighted least squares. Lectures and tutorials as for ST303. For Registered Research students. Permission is required from the Head of the Mathematics & Statistics Department.

Overview

Overview
--------
Scatterplots and regression. The multiple regression model and its applications. Matrix notation, mean vectors and covariance matrices. Least-squares estimation. The multivariate normal distribution. Hypothesis testing and confidence intervals, prediction. Simple linear regression as a special case. Analysis of variance, R2, sequential sums of squares, general F-tests. Added variable plots. Model checking via testing for lack of fit and residual plots. Regression diagnostics: residuals, leverage, outliers, influence and Cook's Distance. Polynomials and factors in regression. Weighted least squares.

Lectures and tutorials as for ST303.

For Registered Research students. Permission is required from the Head of the Mathematics & Statistics Department.

	Learning Outcomes
	On successful completion of the module, students should be able to: Fit and interpret multiple regression models. Understand the theory of multiple regression. Assess model assumptions. Use model diagnostics.

Teaching & Learning methods

Assessment

	Autumn Supplementals/Resits
	Are supplemental/resit registrations permitted? No

	Pre-Requisites
	This module is for Registered Research students. Permission is required from the Head of the Mathematics and Statistics Department to take this module.

	Timetable
	This timetable is not currently available, please contact the Mathematics And Statistics Department.

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Courses / Module

LINEAR MODELS (R)