- Code MGMT4019
- Unit Value 6 units
- Offered by Research School of Management
- ANU College ANU College of Business and Economics
- Course subject Management
- Areas of interest Business Information Systems, International Business, Management, Marketing
- Academic career UGRD
- Prof Israr Qureshi
- Mode of delivery In Person
- Co-taught Course
First Semester 2019
See Future Offerings
The overarching goal of this course is to expose honours, MPhil and PhD students to a variety of empirical methods and data analytic tools to enable them to undertake high quality management research. This includes developing and validating survey measures, understanding and applying basic experimental methodologies, analyzing, interpreting, and writing-up quantitative data. It will also provide students a solid grounding in the use statistical software packages such as SPSS and AMOS as well as key issues and principles involving the linkage between theory and measurement. In sum, the course covers the designs and analyses that are commonly used in marketing, organizational behavior, human resource management and industrial/organizational psychology disciplines. It will emphasise appropriate data collection procedures, data analysis tools and communicating findings effectively, with the course taking the perspective of a management or behavioural researcher.
Upon successful completion, students will have the knowledge and skills to:
- Identify the circumstances that call for advanced quantitative research methods
- Discuss the formulation of the research question to be investigated
- Formalise hypotheses that are in line with the research question
- Use the appropriate method of research to collect data relevant to the hypotheses
- Critically evaluate the analytical strengths and limitations of the different empirical research methods
- Develop appropriate analytical strategies to test the specific hypothesis
- Use relevant software tools to implement hypothesis testing
- Critically interpret and discuss results of analyses through appropriate engagement with extant knowledge and theories
- Synthesise findings, their meanings and subsequent recommendations competently in a structured written report
- Quizzes (40) [LO 1,2,3,5,6,8]
- In-class written interpretation of the data / findings / results (60) [LO 1,2,3,4,5,6,7,8,9]
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Students taking this course are expected to commit at least 10 hours per week to completing the work. This will include 3 hours per week in class and at least 7 hours a week on average (including non-teaching weeks) on course reading, research, writing and assignment work. While the class schedule may vary, there will be an average student workload of 130 hours over the semester.
Requisite and Incompatibility
Readings and texts will be posted on the Wattle site for this course.
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:
- 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.
- Domestic fee paying students
- International fee paying students
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.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|4848||25 Feb 2019||04 Mar 2019||31 Mar 2019||31 May 2019||In Person||View|