Business Forecasting

Subject MAST90009 (2011)

Note: This is an archived Handbook entry from 2011.

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

This subject has the following teaching availabilities in 2011:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

On-campus

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours comprising 1 two-hour lectures per week and 1 one-hour computer lab/practical class per week.
Total Time Commitment:

120 hours
Prerequisites:
None.
Corequisites: None
Recommended Background Knowledge:

It is recommended that students have completed a theoretical statistics subject (equivalent to 620-202 Statistics) and a probability subject (equivalent to either 620-201 Probability or 620-205 Probability for Statistics).
Non Allowed Subjects: None
Core Participation Requirements:

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study and reasonable steps will be made to enhance a student’s participation in the University’s programs. Students who feel their disability may impact upon their active and safe participation in a subject are encouraged to discuss this with the relevant subject coordinator and the Disability Liaison Unit.

Contact

Email: aihuaxia@unimelb.edu.au
Subject Overview: Forecasting is an indispensable part of decision making in business management and government planning. This subject discusses the concept of forecasting and deals with standard forecasting tools. Topics covered include autoregressive, autoregressive moving average and autoregressive integrated moving average time series models, elements of spectral analysis and linear predictors.
Objectives:

After completing this subject, students should:

• understand the basic principles of the construction of time series models;

• be able to analyse the properties of the models and produce predictions based on them;

• be familiar with the most commonly used models and be able to apply the models in various situations;

• gain the ability to pursue further studies in this and related areas.
Assessment: Up to 40 pages of written assignments (30%: three assignments worth 10% each, due early, mid and late in semester), a 3 hour written examination (70%, in the examination period).
Prescribed Texts: TBA
Recommended Texts:

P. J. Brockwell and R. A. Davis, Introduction to Time Series and Forecasting, Springer-Verlag, New York, 2002.
Breadth Options:

This subject is not available as a breadth subject.
Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop
generic skills that will assist them in any future career path. These include:

* problem-solving skills: the ability to engage with unfamiliar
problems and identify relevant solution strategies;

* analytical skills: the ability to construct and express logical
arguments and to work in abstract or general terms to increase the
clarity and efficiency of analysis;

* collaborative skills: the ability to work in a team;

* time-management skills: the ability to meet regular deadlines while
balancing competing commitments.
Notes:

Students will be expected to regularly access a computer running standard statistical software.
Related Course(s): Master of Operations Research and Management Science
Master of Science (Mathematics and Statistics)

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