Advanced Quantitative Methods
Overview
This is a core unit of study in the Honours in Psychology courses. This unit complements other units in the course by providing practical data analysis skills. The unit prepares students to use analytic techniques that may be required for their 4th-year thesis and for future employment. Basic and advanced skills in data preparation, statistical analyses, interpretation of data, and report preparation will be promoted through lectures and computer labs.
Requisites
Rules
Pre-requisite
300 Credit Points in BH-PSY Bachelor of Psychology (Honours) Standard Entry
OR
Admission into BH-PSYSC Bachelor of Psychological Sciences (Honours)
OR
Admission into BH-HSC Bachelor of Health Science (Honours)
Equivalent
HAY453 - Advanced Quantitative Methods
01-June-2025
Learning outcomes
Students who successfully complete this unit will be able to:
- Perform multivariate data analyses using SPSS and AMOS and accurately evaluate statistic outputs
- Identify and select appropriate multivariate data analyses to assess specific hypotheses and/or research questions
- Appraise and convey statistical results that conform to the standards of the American Psychological Association
- Demonstrate the ability to design research studies by appraising the strengths, weaknesses, and assumptions of relevant multivariate data analysis techniques
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Live Online Lecture | 1.00 | 12 weeks | 12 |
| On-campus Class | 2.00 | 12 weeks | 24 |
| Specified Activities Various | 2.00 | 12 weeks | 24 |
| Unspecified Activities Various | 7.50 | 12 weeks | 90 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Assignment 1 | Individual | 30% | 1,2,3 |
| Assignment 2 | Individual | 30% | 2,4 |
| Online Tests | Individual | 40% | 1,2,3,4 |
Content
- Overview of data analysis, screening and missing values
- Basic and advanced forms of multiple regression analyses
- Basic and advanced forms of Analysis of Variance (ANOVA)Â
- Exploratory and Confirmatory Factor Analyses
- Path Analysis and Structural Equation Modelling (SEM)
- Meta-analysis
- Graduate Attribute 2 (Communication 2 - Communicating using different media)
- Graduate Attribute 5 (Digital Literacies 1 - Information literacy)
- Graduate Attribute 6 (Digital Literacies 2 - Technical literacy)
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.