Subject details

  • Topics
    • Review of multiple regression: understanding partial and part correlation coefficients, selecting and using different regression strategies
    • Tests for mediation and moderation using multiple linear regression
    • Exploratory factor analysis
    • Multivariate Analysis of Variance (MANOVA): Between subjects, within subjects and mixed-design MANOVA
    • Discriminant analysis
    • Binary Logistic Regression
    • Canonical Correlation Analysis
  • Study resources
    • Instructional Methods
      • Disscusion forum/Discussion Board
      • Online Quizzes/Tests
      • Online assignment submission
      • Web links
    • Print Materials
      • Welcome letter
    • Online Materials
      • Printable format materials

Students who successfully complete this subject will be able to:

  1. Summarise the objectives of a study, specify variables of interest in a study and identify their level of measurement
  2. Prepare data files for analyses (i.e. data screening, checking assumptions etc.)
  3. Test the assumptions underlying a statistical analysis and state the limitations of a study
  4. Identify the most appropriate analysis for the research question and execute the analysis using an appropriate software package
  5. Interpret and report the results of statistical analyses.  
  • Assignment 1 - Quizzes — Online (10%)
  • Assignment 2 - Invigilated Exam (50%)
  • Assignment 3 - Assignments — 2 (40%)

Textbooks are subject to change within the academic year. Students are advised to purchase their books no earlier than one to two months before the start of a subject

Entry Requirements

Equivalent Subjects

You cannot enrol in this unit if you have successfully completed any of the following subject(s) because they are considered academically equivalent:

  • SWI-HMS780

You must have successfully completed the following subject(s) before starting this subject:

Special requirements

No special requirements

This subject teaches students to identify and apply the multivariate statistical techniques most commonly used in social and health research, to understand the assumptions underlying their use, and appreciate the strengths and limitations of these methods. Knowledge of these methods is particularly helpful for gaining employment in statistical consulting. 

Please note: assessment values are indicative only, details will be advised at the start of the subject.

Related degrees