Quantitative Decision Making 2

Subject ECON90049 (2013)

Note: This is an archived Handbook entry from 2013.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject is not offered in 2013.

Time Commitment: Contact Hours: Two 1-hour lectures and one 1-hour workshop per week
Total Time Commitment: Estimated total time commitment of 120 hours per semester
Prerequisites: ECOM90009 Quantitative Methods for Business
Study Period Commencement:
Credit Points:
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/


Graduate School of Business and Economics
Level 4, 198 Berkeley Street
Telephone: +61 3 8344 1670
Online Enquiries
Web: www.gsbe.unimelb.edu.au

Subject Overview: This subject illustrates the use of quantitative methods to aid managerial decision making. Topics include review of statistics; F and Chi-squared distributions; review of simple linear regression multiple linear regression model; hypothesis testing, forecasting, diagnostics with regression (including heteroskedasticity, serial correlation and model specification).

On successful completion of this subject students should be able to:

  • Apply the least-squares method of estimation to the context of the simple linear regression model;
  • Apply the principles of the least-squares method of estimation and inference to the multiple linear regression model;
  • Apply EViews to estimate, test hypotheses and forecast in the context of the linear regression model;
  • Explain various problems that arise from applying the linear regression model to data, including multicollinearity, specification errors, heteroskedasticity, nonstationarity and autocorrelation.
  • One 2-hour end-of-semester examination (70%)
  • Assignments not exceeding 1500 words in the first half of the semester (15%)
  • Assignments not exceeding 1500 words in the second half of the semester (15%)
Prescribed Texts: You will be advised of prescribed texts by your lecturer.
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On successful completion of this subject, students should have improved the following generic skills:

  • High level of development: statistical reasoning; application of theory to practice; interpretation and analysis; synthesis of data and other information; evaluation of data and other information; and use of computer software.
  • Moderate level of development: written communication; critical thinking; problem solving; and receptiveness to alternative ideas; evaluation of ideas, views and evidence, synthesis of ideas, views and evidence.
  • Some level of development: collaborative learning and team work; and accessing data and other information; from a range of sources; oral communication; strategic thinking.
Related Course(s): Master of Management (Economics)

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