Multivariate Statistics
Duration
- One Semester or equivalent
Contact hours
- 3 Hours per Week
On-campus unit delivery combines face-to-face and digital learning. For Online unit delivery, learning is conducted exclusively online.
2023 teaching periods
| Hawthorn HOL Study Period 1 |
Hawthorn HOL Study Period 3 | |
|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
Aims and objectives
This unit 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.
1. Summarise the objectives of a study and prepare data files for analysis.
2. Test the assumptions underlying a statistical analysis and state the limitations of a study
3. Develop statistical models to describe associations between variables
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
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
| Type (On-campus) | Hours per week | Number of Weeks | Total |
| On Campus Class |
1 |
12 | 12 |
| Online Learning Activities | 3 | 12 | 36 |
| Unspecified Activities Independent Learning |
8.5 | 12 |
102 |
| TOTAL | 150 hours |
| Type | Hours per week | Number of Weeks | Total |
| Live Online Class |
1 |
12 |
12 |
| Online Directed Online Learning and Independent Learning |
11.5 |
12 |
138 |
| TOTAL | 150 hours |
Assessment
| Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
| Assignment | Individual | 50% | 1, 2, 3, 4, 5 |
| Examination | Individual | 40% | 2, 4, 5 |
| Online Quizzes (10) | Individual | 10% | 2, 4, 5 |
Content
- Multiple linear regression: screening, testing assumptions, regression strategies: standard, hierarchical and step-wise regression.
- mediation, moderation and PROCESS macro.
- General Linear Models: Interaction, Analysis of Covariance (ANCOVA).
- Multivariate Analysis of Variance (MANOVA): Between subjects, within subjects and mixed-design MANOVA.
- Factor analysis: Exploratory and confirmatory factor analysis.
- Introduction to path analysis: Structural Equation Modelling
Study resources
- Reading materials.