This course is not offered in 2018.
This course is intended to advance familiarity with multivariate statistical methods. A short-term objective is to enable students to conduct appropriate kinds of multivariate analyses of project data with a reasonable level of understanding. Such as:
• Knowing what kind(s) of multivariate techniques address the research questions in the project;
• Understanding how to utilise such techniques, make intelligent choices where options exist, and interpret the results;
• Knowing what the techniques can and cannot do;
• Having a basic understanding of what happens ‘under the bonnet’ when a computer package performs a particular analysis;
Additionally the course will provide a strong grounding in multivariate statistical methods that will enable students to teach themselves how to conduct new kinds of analysis using SPSS, R, or an equivalent package; and understand and critique professional research that presents results of analyses.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Upon successful completion of this course, students will have the knowledge and skills to:- Understand and apply multivariate statistical techniques
- Critique the limitations and strengths of multivariate techniques
- Become an independent user of of statistical packages such as SPSS and R
- Understand and critique professional research that uses multivariate techniques
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
12 x 2-hour lecture/laboratory classesThe workload is expected to be 130 hours, including study time, spread over the semester or session.
Requisite and Incompatibility
You will need to contact the Research School of Psychology to request a permission code to enrol in this course.
Prescribed Texts
Tabachnick, B.G. & Fidell, L.S. (most recent edition) Using Multivariate StatisticsPreliminary Reading
Howell, D.C. (2007) Statistical Methods for Psychology, 6th Edition. PWS-Kent.
Maxwell, S.A. & Delaney, H.D. (1990, 2004) Designing Experiments and Analyzing
Data: A Model Comparison Perspective. Belmont, California: Wadsworth.
Smithson, M. (2003) Confidence Intervals
Assumed Knowledge
Assessment will be based on:- Exam 48% LO 1-4
- Assignment 48% LO 1-4
- Online quizzes 4% LO 1-4
Fees
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 1
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2018 | $3780 |
- International fee paying students
| Year | Fee |
|---|---|
| 2018 | $5400 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
