STA448 Multivariate Statistical Analysis (8)

This subject introduces students to multivariate statistical modelling techniques through an applied approach to data analysis. The emphasis is on demonstration of techniques and their applicability via investigations of the various methodologies. The use of real life data and software packages is also emphasised in this subject to illustrate the power and limitations of multivariate methods.

Subject Outlines
Current CSU students can view Subject Outlines for recent sessions. Please note that Subject Outlines and assessment tasks are updated each session.


Session 2 (60)
Wagga Wagga Campus

Continuing students should consult the SAL for current offering details: STA448. 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 Computing and Mathematics

Enrolment Restrictions

Not available to students who have completed STA347

Assumed Knowledge

STA201 or STA401

Incompatible Subjects


Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to use a variety of matrix notations and perform matrix algebra used in multivariate analysis;
  • be able to analyse multivariate data with summary estimates and correct visualisation;
  • be able to classify given complex problems, arising from a variety of professional or research contexts, by checking assumptions to select the appropriate analysis techniques;
  • be able to apply the chosen technique to solve the complex problem;
  • be able to report and explain the results of the analysis to a variety of audiences, including those with or without statistical backgrounds;
  • be able to use statistical packages in analysis of real data arising from a variety of professional or research contexts.


This subject will cover the following topics:
  • Introductory matrix notations and matrix algebra.
  • Multivariate data: summary statistics and graphical visualisation.
  • The Multivariate Normal Distribution.
  • Principal Components analysis.
  • Discriminant analysis.
  • Multivariate analysis of variance (MANOVA).
  • Canonical correlation analysis.


Current Students

For any enquiries about subject selection or course structure please contact Student Central or or phone on 1800 275 278.

Prospective Students

For further information about Charles Sturt University, or this course offering, please contact info.csu on 1800 275 278 (free call within Australia) or enquire online.

The information contained in the 2018 CSU Handbook was accurate at the date of publication: August 2018. The University reserves the right to vary the information at any time without notice.