Coronavirus (COVID-19) Update
Due to the Coronavirus (COVID-19) pandemic, any references to assessment tasks and on-campus delivery may no longer be up-to-date on this page.
Students should consult iLearn for revised unit information.
Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students
Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit convener/Lecturer
Fazeel Mohamed Jaleel
Contact via 98504849
4ER 452
TBA
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---|---|
Credit points |
Credit points
10
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Prerequisites |
Prerequisites
Admission to GradCertFin or GradDipAppFin or MAppEcon or MAppFin or MAppFin(Adv) or MkgFin or MBusAnalytics
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit is designed to bring students with no econometrics background to an intermediate level in econometrics. Starting from first principles, the unit outlines standard econometric methods to the extent necessary for students to understand key concepts, apply basic methods, and interpret empirical research results in economics, finance and business. The unit material also includes elementary discussions of violations of the standard assumptions for a regression model, such as autocorrelation and heteroscedasticity. |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Coronavirus (COVID-19) Update
Assessment details are no longer provided here as a result of changes due to the Coronavirus (COVID-19) pandemic.
Students should consult iLearn for revised unit information.
Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students
Coronavirus (COVID-19) Update
Any references to on-campus delivery below may no longer be relevant due to COVID-19.
Please check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status
This unit is taught as a mix of tutorials and lectures. The lectures are designed to introduce the underlying knowledge in probability, statistics and econometrics, and to explain the methods which will be used to analyse and interpret data. Tutorials are based mainly on numerical problems which allow students to practice and understand the methods taught in the lectures. The tutorials include empirical applications which require the use of econometric software packages. Students will be taught how to use these packages in tutorials which are held in the computer labs.
Lectures – large group learning (2 hour each teaching week)
Lectures are intended to provide an overview of statistical and econometrics techniques that are critical to the core themes of the unit. Students are expected to read the relevant material before each lecture.
Tutorials – 1 hour per week
Tutorials will go through assigned problems which may be mathematical exercises, or which may require use of the econometric software available in the computer lab to estimate a model.
Self-study activities – learning by doing (about 6 hours each teaching week and 9 hours each week during the 2-week mid-semester recess)
This subject heavily relies on independent learning where students read the lecture notes, relevant chapters in the useful text books and prepare answers to the pre-set tutorial questions.
Useful but not required texts include:
Material such as lecture slides, examples, and tutorial questions will be available on the unit home page. The lecture notes, together with the lectures and additional references will provide students with a clear indication of the basic content of the unit.
It is recommended that students attend all lectures and tutorials for several reasons including:
Coronavirus (COVID-19) Update
The unit schedule/topics and any references to on-campus delivery below may no longer be relevant due to COVID-19. Please consult iLearn for latest details, and check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status
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Week No. |
Lecture Topic |
Activities |
|
1 |
Introduction & Descriptive Statistics |
Lecture |
|
2 |
Descriptive Statistics (continued) |
Lecture & Tutorial |
|
3 |
Probability and Random Variables |
Lecture & Tutorial |
|
4 |
Probability Distributions |
Lecture & Tutorial |
|
5 |
Sampling Distributions: Point Estimates and Confidence Intervals |
Lecture & Tutorial |
|
6 |
Class Test in Lecture |
Tutorial & Class Test |
|
7 |
Hypothesis Testing |
Lecture & Tutorial |
|
|
MID-SEMESTER BREAK |
|
|
8 |
Introduction to Regression Analysis |
Lecture & Tutorial |
|
9 |
Multiple Linear Regression |
Lecture & Tutorial |
|
10 |
Class Test in Lecture |
Tutorial & Class Test |
|
11 |
Multiple Linear Regression (continued) |
Lecture & Tutorial |
|
12 |
Regression Model Diagnostics |
Lecture & Tutorial
|
|
13 |
Review Exam preparation |
Lecture & Tutorial Assignment Due |
|
Exam Period |
|
Final Exam |
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