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Econometrics G (6551.6)

Level: Graduate Level
Credit Points: 3
HECS Bands: 2, 4
Faculty: Faculty of Science and Technology
Discipline: Academic Program Area - Technology

Availability

    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.

    Syllabus

    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.

    Prerequisites

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

    Corequisites

    None.

    Assumed Knowledge

    None.

    Incompatible Units

    None.

    Equivalent Units

    None.



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