Handbook home
Advanced Design and Data Analysis (PSYC40005)
HonoursPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1 (Early-Start)
Dr Adam Osth
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 1 (Early-Start) |
---|---|
Fees | Look up fees |
This subject provides an introduction to multivariate data analysis in the behavioural and social sciences, including the nature, rationale and application of a number of widely used multivariate data analysis models. For each model, issues covered include the nature of the model and its assumptions; situations in which the model might be applied; diagnostics for model adequacy; estimation and inference; interpretation; the use of the software package SPSS for model-fitting. Models will be selected from multiple regression; logistic regression; an introduction to path analysis and structural equation modelling; multivariate analysis of variance and discriminant analysis; multilevel models; principal components analysis and factor analysis; models for multivariate categorical data; cluster analysis and multidimensional scaling.
The first two lectures/tutorials of the subject will be taught on one day (six hours) in Orientation Week, thereby allowing students time to work on assessment tasks at the beginning of the semester.
Intended learning outcomes
Upon completion of the subject, students should demonstrate the following competencies in psychology:
Knowledge
Students should demonstrate knowledge of:
- The forms of major multivariate techniques including multivariate analysis of variance and variants, multilevel models, methods for categorical data analysis and structural equation modelling;
- The role of, and methods for, exploratory analysis of multivariate observations such as factor analysis, multidimensional scaling, and clustering;
- The appropriate analysis tool required for a particular dataset.
Skills
On completion of the subject students should be able to:
- Execute complex multivariate methods for data analysis in SPSS;
- Explore and visualize data using clustering and multidimensional scaling;
- Reduce complex data to a set of interpretable factors using principal components analysis and factor analysis.
Application of knowledge and skills
On completion of the subject, students should be able to apply their knowledge and skills to:
- Design research studies requiring complex quantitative observations;
- Apply major multivariate techniques to large datasets with psychological variables
- Critically evaluate and interpret complex quantitative information.
Generic skills
On completion of this subject, students should have a greater ability to:
- present and analyse complex quantitative information;
- synthesize, interpret, and communicate information in ways that others can understand
- think critically about which tools are required for different types of problems
- critically evaluate assumptions, advantages, and limitations of different analytic techniques
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Entry to the Psychological Sciences fourth year program via one of:
- Bachelor of Science (Degree with Honours) (BH-SCI); or
- Bachelor of Arts (Degree with Honours) (BH-ARTS); or
- Graduate Diploma in Psychology (Advanced) (GDA-PSYCH); or
- Master of Applied Psychology (MC-AP).
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
An accredited psychology major sequence
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Description | Timing | Percentage |
---|---|---|
A written report of no more than 1000 words
| Early in the teaching period | 20% |
A written report of no more than 1500 words
| Mid semester | 30% |
And an examination of no more than two hours
| During the examination period | 50% |
Hurdle requirement: Each piece of assessment must be completed. Attendance at 80% or more of the laboratory classes is a hurdle requirement. In case of failure to meet the hurdle requirement, additional work related to the missed class activities (e.g., short 500 word essay on missed topic) will be required before a passing grade can be awarded. | Throughout the teaching period | N/A |
Last updated: 3 November 2022
Dates & times
- Semester 1 (Early-Start)
Principal coordinator Adam Osth Mode of delivery On Campus (Parkville) Contact hours Six-hour workshop day in Orientation Week; 24 hours of lectures, 12 hours of laboratory classes. Total time commitment 170 hours Teaching period 28 February 2020 to 7 June 2020 Last self-enrol date 6 March 2020 Census date 30 April 2020 Last date to withdraw without fail 5 June 2020 Assessment period ends 3 July 2020 Semester 1 (Early-Start) contact information
Dr Adam Osth
Time commitment details
Estimated total time commitment of 170 hours.
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
There are no prescribed texts
- Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Diploma in Psychology (Advanced) Course Master of Commerce (Accounting) Informal specialisation Psychology
Last updated: 3 November 2022