Note: This is an archived Handbook entry from 2015.
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2015:Semester 1, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 3 contact hours per week (2 hours lecture; 1 hour tutorial) |
Total Time Commitment:
144 hours per semester, including self-directed study and research
|Recommended Background Knowledge:||None|
|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: http://services.unimelb.edu.au/disability
CoordinatorDr Daejeong Choi
MBS @ Berkeley Street
Level 4, 198 Berkeley Street
Telephone: +61 3 8344 1670
This subject is aimed at students undertaking graduate research programs. The overall aim is to introduce students to core quantitative methods and techniques commonly used in management and marketing research. It provides students with a working knowledge of the spectrum of alternative techniques for collecting and analysing data. Whilst this subject will not provide the depth required of a specialist in any particular technique, by the end of this subject, students will have a working knowledge of the foundations of descriptive and inferential statistics, with a focus on applying ANOVA, MANOVA and regression analysis.
In this subject students will be able to:
|Prescribed Texts:|| |
|Breadth Options:|| |
This subject is not available as a breadth subject.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
Doctor of Philosophy - Business and Economics |
Master of Commerce (Management)
Master of Commerce (Marketing)
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