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

    2017
  • Enrolment Period

    1
  • Version

    1
  • Credit Points

    15
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
  • Unit Coordinator

    Dr Aiden James FISHER

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.

ON CAMPUS
TypeDescriptionValue
TestMid Semester Test20%
AssignmentWritten Assignment30%
ExaminationEnd of semester examination50%

Core Reading(s)

  • Hanke, J. E., & Wichern, D. W. (2009). Business forecasting. (9th ed.). Upper Saddle River: Prentice Hall.

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

MAT2440|1|1

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

    2017
  • Enrolment Period

    2
  • Version

    1
  • Credit Points

    15
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
  • Unit Coordinator

    Dr Aiden James FISHER

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.

ON CAMPUS
TypeDescriptionValue
TestMid Semester Test20%
AssignmentWritten Assignment30%
ExaminationEnd of semester examination50%

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

MAT2440|1|2