Handbook : Unit informationEdith Cowan University

School: Science

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

• Unit Title

  Time Series Forecasting

• Unit Code

  MAT2440

• Year

  2016

• Enrolment Period

  1

• Version

  1

• Credit Points

  15

• Full Year Unit

  N

• Mode of Delivery

  On Campus
  

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Description

Students will be provided an introduction to Time Series Forecasting. It will focus on time series decomposition, exponential smoothing, regression and Box-Jenkins models.Students will learn how to choose an appropriate time series model, apply the model, carry out a diagnostic check of the model and apply the model for prediction and forecasting.

Prerequisite Rule

Students must pass 1 unit from BES1100, MAT1114

Equivalent Rule

Unit was previously coded MAT2215

Learning Outcomes

On completion of this unit students should be able to:

1. Apply the chosen model for forecasting and prediction.
2. Carry out a diagnostic check of the chosen model.
3. Explain the details of a number of time series forecasting models.
4. Fit an appropriate model.

Unit Content

1. Applications of the time series forecasting models.
2. Autoregressive, Moving Average, combined ARMA and Box-Jenkins time series forecasting models.
3. Diagnostic checks for the suitability of a given time series forecasting model to a particular application.
4. Exponential Smoothing Methods.
5. Simple and Multiple Regression.
6. Time Series Decomposition.

Additional Learning Experience Information

Lectures, tutorials and computer workshops.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant Board of Examiners.

Text References

• ^ Hanke, J.E., & Wichern, D.W. (2009). Business forecasting (9th ed.). Upper Saddle River: Prentice Hall.
• Box, G., Jenkins, G., & Reinsel, G.(1994). Forecasting and control (3rd ed.). New Jersey: Prentice Hall.
• Bisgaard, S & Kulahci, M. (2011). Time series analysis and forecasting by example. Hoboken: John Wiley.
• Abraham, B., & Ledolter, J. (2005). Statistical methods for forecasting. New York: John Wiley.
• Harris R., & Sollis, R. (2003). Applied time series modelling and forecasting. New York: John Wiley.
• Bowerman, B.L., O'Connell, R.T.O. & Koehler, A. B. (2005). Forecasting, Time series and regression (4th ed.). Brooks/Cole.

^ Mandatory reference

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