MAT3211

Linear regression

Coordinator: Dr Robert Griffiths

4 points
* Two 1-hour lectures per week
* First semester
* Clayton
* Prerequisites: MAT2020, MAT2061, MAS2032 or MAT2222
* Prohibitions: GAS3632, MAS3111, MAT2236

Objectives On the completion of this subject students will be able to understand the theory of multiple regression; analyse data sets which require multiple regression techniques with the statistical computer package Minitab; understand the theory of significance tests in multiple regression; perform statistical tests related to regression on data.

Synopsis The simple linear regression model. Least squares fitting of multiple regressions. Significance tests and confidence intervals for regression parameters. Residual analysis for adequacy of model. Weighted least squares. Correlated errors.

Assessment Examination (2 hours): 85%
* Assignments and/or tests: 15%

Recommended texts

Myers R H Classical and modern regression with applications 2nd edn, PWS-Kent, 1990
Weisberg S Applied linear regression 2nd edn, Wiley, 1985