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Advanced Quantitative Research Methods (MGMT90199)
Graduate courseworkPoints: 12.5Not available in 2023
To learn more, visit 2023 Course and subject delivery.
Overview
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This subject is aimed at students in research graduate programs. The subject introduces students to advanced inferential techniques used in management and marketing research. Topics will include but not limited to regression models, critical assumptions, mediation and moderation, limited dependent variables, panel data, endogeneity, instrumental variable estimation. This subject will include opportunities to apply one or more of these techniques in a research project using specialised computer software called STATA.
Intended learning outcomes
In this subject students will be able to:
- Understand the range of advanced quantitative research methods deployed in social and organisational research
- Competently apply advanced statistical techniques to collection, analysis of data
- Interpret and present the results of different statistical analyses using appropriate tabular and graphical displays
Generic skills
On successful completion of this subject, students should have improved the following generic skills:
- Problem solving skills, which should be enhanced through the study of research design and research methods
- Writing skills appropriate for the preparation of academic articles and research reports in Management and Marketing, including the doctoral thesis
- Analytical skills, which should be developed through the evaluation of quantitative and qualitative empirical research literature
Last updated: 30 March 2023
Eligibility and requirements
Prerequisites
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MGMT90203 | Foundations in Quantitative Methods | Semester 2 (On Campus - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
A basic understanding of multivariate statistics as included in for example:
Sarstedt, M., & Mooi, E. (2014). A Concise Guide to Market Research (2nd ed.): Springer, Cohen, J., Cohen, P., West, S.G., & Aitken, LS (2003), Applied multiple regression/correlation analysis in the behavioural sciences (Third Edition). Mahwah, N.J. Routledge; Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis. Upper Saddle River, NJ: Pearson.
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: 30 March 2023
Assessment
| Description | Timing | Percentage |
|---|---|---|
Class participation (attendance and active participation in class discussions), throughout the semester
| Throughout the semester | 10% |
Paper presentation and critique #1
| Week 6 | 20% |
Paper presentation and critique #2
| Week 12 | 20% |
End of semester take home examination
| End of semester | 50% |
Last updated: 30 March 2023
Dates & times
Not available in 2023
Time commitment details
Estimated total time commitment of 170 hours per semester
Last updated: 30 March 2023
Further information
- Texts
Prescribed texts
TBC
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 30 March 2023