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To enrol in this unit, you must be accepted into a course from the provider.
Read before you start
Level of study: What does Postgraduate mean?
EFTSL: What does EFTSL mean?
Delivery Method: What does delivery method mean?
Availability: What is a Study period?For enrolment (2012): For forward planning* (2013): What is Forward Planning?
Government loans available:
- Domestic student fee:
- $1,950.00 (AUD)
- International student fee:
- $2,175.00 (AUD)
This unit aims to introduce you to various forecasting methods and their application in business and industry. You will become familiar with common tools and packages used in forecasting so that you are able to:
- use historical data to identify appropriate forecasting models
- use various accuracy measures to check the adequacy of the selected model
- use the final model to forecast future values
- improve your team-working and analytical skills.
Please note: Assessment values are indicative only; details will be advised at the start of the unit.
You are recommended to have completed the following unit(s) or have equivalent knowledge before starting this unit:
- Additional materials
- Other special requirement — You will be asked to sign and return an agreement form in order to obtain a free copy of SAS 9.2. Note: SAS will only run on a Windows platform.
- Assignment 1 (20%)
- Assignment 2 (20%)
- Invigilated Exam (50%)
- Quiz (10%)
At the completion of this unit students will be able to:
- extract time series data from ABS web sites
- compute indices based on time series data
- plot time series and describe their characteristics
- use various methods to obtain short-term forecasts
- compare the accuracy of these forecasts using appropriate measures
- construct regression models for time series data and test the assumptions of these models
- variable selection using stepwise and best subset regression procedures
- use the ACF and PACF to identify appropriate ARIMA models for a series
- fit and compare the accuracy of likely ARIMA models for short-term forecasting purposes using appropriate criteria
- improve the accuracy of regression forecasts using lagged terms and AR models for the errors.
This unit addresses the following topics.
|1||Time series forecasting methods|
|2||Measures of accuracy|
|3||Introduction to smoothing methods|
|4||Methods for stationary forecasting|
|5||Methods for trend forecasting|
|6||Seasonal forecasts by smoothing|
|8||Regression and forecasting with cycles|
|9||Removal of non-stationarity and the autocorrelation function|
|13||Lagged regression models|
This unit is delivered using the following methods and materials:
- Discussion Forum/Discussion Board
- Online Quizzes/Tests
- Online assignment submission
- Web links
Print based materials
- Welcome Letter
- Printable format materials
Textbooks are subject to change within the academic year. Students are advised to purchase their books no earlier than one to two months before the start of a unit.
Click on the titles of the listed books below to find out more:
This unit is a core requirement in the following courses:
- Graduate Diploma of Science (Applied Statistics), Swinburne University of Tnlgy
- Master of Science (Applied Statistics), Swinburne University of Tnlgy
This unit may be eligible for credit towards other courses:
- Many undergraduate courses on offer through OUA include 'open elective' where any OUA unit can be credited to the course. You need to check the Award Requirements on the course page for the number of allowed open electives and any level limitations.
- In other cases, the content of this unit might be relevant to a course on offer through OUA or elsewhere. In order to receive credit for this unit in the course you will need to supply the provider institution with a copy of the Unit Profile in the approved format, which you can download here. Note that the Unit Profile is set at the start of the year, and if textbooks change this may not match the Unibooks textbook list.
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