STA408 Linear Models (8)

The linear model is all pervasive in the application of statistical techniques to the analysis of data. This fundamental method underpins many others such as nonlinear regression and methods for analysing non-normal data. This subject will give an overview of the linear model and its application in regression and basic experimental design and analysis for data based on independent observations.

No offerings have been identified for this subject in 2019.

Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System



One session


School of Information Studies

Assumed Knowledge
STA201 or STA420

Learning Outcomes

Upon successful completion of this subject, students should:
  • Be able to recognise situations for which a linear model is appropriate;
  • Be able to perform basic linear algebra tasks;
  • Be able to design and check simple experiments;
  • Be able to perform the analysis of such experiments and report the results in terms of the original problem;
  • Be able to critically test any assumptions underpinning the use of the linear model;
  • Be able to perform design and analysis tasks on recognised software platforms;
  • Be aware of the limitations of the independence assumption and appreciate the various alternatives available.


This subject will cover the following topics:

Overview of linear models and their applications in general; Review of basic linear algebra; Univariate linear model for independent data - underlying concepts and assumptions; Regression, observational data; Experimental design and analysis - fixed effects, random effects, mixed models and different error strata; Tests of assumptions; Software platforms - SPSS, GENSTAT, Splus; Multivariate linear model (introductory), multivariate regression (GLS), MANOVA.

Residential School

This subject contains a 0 day Optional Residential School.


For further information about courses and subjects outlined in the CSU handbook please contact:

Current students

Future students

The information contained in the CSU Handbook was accurate at the date of publication: May 2019. The University reserves the right to vary the information at any time without notice.