Business Forecasting
Subject 600-655 (2009)
Note: This is an archived Handbook entry from 2009. Search for this in the current handbook
| Credit Points: | 12.50 | ||||||||||||
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| Level: | 9 (Graduate/Postgraduate) | ||||||||||||
| Dates & Locations: | This subject has the following teaching availabilities in 2009: Semester 2, - Taught on campus.
On-campus Timetable can be viewed here. For information about these dates, click here. | ||||||||||||
| Time Commitment: | Contact Hours: 36 hours comprising 2 one-hour lectures per week and 1 one-hour computer lab/practical class per week. Total Time Commitment: 3 contact hours plus 7 hours private study per week. | ||||||||||||
| Prerequisites: |
None. | ||||||||||||
| Corequisites: | None | ||||||||||||
| Recommended Background Knowledge: |
It is recommended that students have completed a theoretical statistics subject (equivalent to 620-202 [2008] Statistics) and a probability subject (equivalent to either 620-201 [2008] Probability or 620-205 [2008] 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 participation are encouraged to discuss this with the subject coordinator and the Disability Liaison Unit. |
Coordinator
Assoc Prof Aihua Xia| 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 and general autoregressive conditional heteroscedasticity, elements of spectral analysis and linear predictors. |
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| 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: | TBA |
| Breadth Options: | This subject is not available as a breadth subject. |
| Fees Information: | Subject EFTSL, Level, Discipline & Census Date |
| Generic Skills: |
Students should learn to: - Adopt modeling ideas, think critically and organize knowledge from consideration of basic modelling skills. - Present a mathematical argument, by reflecting on those presented in the lecture series. - Develop creative ways of solving unfamiliar problems. - Plan effective work schedules, to meet the regular deadlines for submission of assessable work. - Work in a team environment. |
| Notes: | Students will be expected to regularly access a computer running standard statistical software. |
| Related Majors/Minors/Specialisations: |
R05 RM Master of Science - Mathematics and Statistics |
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