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

  MAT6100

• Year

  2021

• Enrolment Period

  1

• Version

  1

• Credit Points

  20

• Full Year Unit

  N

• Mode of Delivery

  On Campus
  Online

• Unit Coordinator

  Dr Ebenezer AFRIFA-YAMOAH

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Description

This unit will provide 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, carry out a diagnostic check of the model and apply the model for prediction and forecasting using statistical software.

Prerequisite Rule

Students must pass MAT5212 and MAT6105.

Learning Outcomes

On completion of this unit students should be able to:

1. Apply suitable time series models for forecasting and prediction.
2. Use critical thinking skills with regard to fitting appropriate models to a variety of time series data.
3. Implement time series analysis using statistical software.
4. Communicate time series theories, principles and techniques.

Unit Content

1. Time series decomposition.
2. Autoregressive, moving average, combined ARMA and Box-Jenkins time series forecasting models.
3. Exponential smoothing methods.
4. Diagnostic checks for the suitability of a given time series forecasting model to a particular application.
5. Simple and multiple regression.
6. Applications of the time series forecasting models.

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 School Progression Panel.

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