Advanced Quantitative Research Methods

Subject MGMT90199 (2015)

Note: This is an archived Handbook entry from 2015.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2015:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 27-Jul-2015 to 25-Oct-2015
Assessment Period End 20-Nov-2015
Last date to Self-Enrol 07-Aug-2015
Census Date 31-Aug-2015
Last date to Withdraw without fail 25-Sep-2015

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: Classes will run every second week throughout the semester; one 3 hour lecture and one 3 hour workshop each fortnight
Total Time Commitment:

144 hours per semester, including self-directed study

Study Period Commencement:
Credit Points:
Corequisites: 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. Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis. Upper Saddle River, NJ: Pearson.

Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support:


Dr Erik Mooi


MBS @ Berkeley Street
Level 4, 198 Berkeley Street
Telephone: +61 3 8344 1670

Subject Overview:

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.

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; and
  • interpret and present the results of different statistical analyses using appropriate tabular and graphical displays.
  • Paper presentation and critique #1 (individual, 2,000 word written report) due in week 6 (20%)
  • Paper presentation and critique #2 (individual, 2,000 word written report) due in week 12 (20%)
  • A take home examination at the end of semester (50%)
  • Class participation (attendance and active participation in class discussions), throughout the semester (10%)
Prescribed Texts:


Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
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; and
  • Analytical skills, which should be developed through the evaluation of quantitative and qualitative empirical research literature.

Related Course(s): Doctor of Philosophy - Business and Economics
Master of Commerce (Management)
Master of Commerce (Marketing)

Download PDF version.