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Econometrics G (6551.6)

Level: Graduate Level
Credit Points: 3
HECS Bands:

Band 1 2021 (Commenced After 1 Jan 2021) Band 1 2021 (Commenced Before 1 Jan 2021) Band 2 2013-2020 (Expires 31 Dec 2020)

Faculty: Faculty of Science and Technology
Discipline: Academic Program Area - Technology


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As a result of the Australian Government's and or the ACT Government’s directives requiring physical distancing and restrictions on movement because of the COVID-19 pandemic, you may find that learning activities and/or assessment items in some units you are studying have changed. These changes will not be updated in the published Unit Outline but will be communicated to you via your unit’s UCLearn(Canvas) teaching site. The new learning activities and/or assessment items will continue to meet the unit's learning outcomes, as described in the Unit Outline.

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Unit Outlines

To view your Unit Outline, click View to log in to MyUC and access this information, or visit your unit's online teaching site.

  • Semester 2, 2019, FLEXIBLE, BRUCE (185534) - View
  • Semester 2, 2018, FLEXIBLE, BRUCE (181714) - View
  • Semester 2, 2017, FLEXIBLE, BRUCE (169996) - View
  • Semester 1, 2016, ON-CAMPUS, BRUCE (154154) - View
  • Semester 1, 2015, ON-CAMPUS, BRUCE (145801) - View

If a link to your Unit Outline is not displayed, please check back later. Unit Outlines are generally published by Week One of the relevant teaching period.


This unit deals with econometric models and their application to problems in business, economics, finance and other areas. The emphasis is on the practical issues concerned with specifying, estimating, testing and applying dynamic models using a computer package. Topics may include simple, multiple and time series regression, multicollinearity, heteroskedasticity, serial correlation and spurious correlation.

Learning Outcomes

On successful completion of this unit, students will be able to:

1. Formulate an appropriate dynamic model for data analysis;

2. Estimate the parameters of a dynamic model using a statistical computer package;

3. Test the parameters of a dynamic model using a statistical computer package;

4. Evaluate the validity of a dynamic model;

5. Apply and explain a technique for forecasting a variable of interest;

6. Produce and interpret the results of analyses in a form which is suitable for publication; and

7. Apply important extensions to the linear regression model.

Assessment Items

Contact Hours

A 2-hour lecture and a 2-hour lab per week.


6275 Statistical Analysis and Decision Making G or 6554 Introduction to Statistics G or 1809 Data Analysis in Science.



Assumed Knowledge


Incompatible Units


Equivalent Units


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