Course Coordinator:Sajid Anwar (sanwar@usc.edu.au) School:School of Business and Creative Industries
UniSC Sunshine Coast |
Blended learning | Most of your course is on campus but you may be able to do some components of this course online. |
Online |
Online | You can do this course without coming onto campus, unless your program has specified a mandatory onsite requirement. |
Please go to unisc.edu.au for up to date information on the
teaching sessions and campuses where this course is usually offered.
You will learn to use econometric software to conduct your own empirical analyses using multiple regression techniques. You will also deepen your understanding of key practical aspects of regression modeling, including the consequences of violating regression assumptions, the use of dummy variables, alternative functional forms, and an introduction to time-series and panel data models.
| Activity | Hours | Beginning Week | Frequency |
| Blended learning | |||
| Learning materials – Interactive online learning activities. | 1hr | Week 1 | 12 times |
| Tutorial/Workshop 1 – Scheduled face to face workshops. | 2hrs | Week 1 | 12 times |
| Online | |||
| Learning materials – Interactive online learning activities. | 1hr | Week 1 | 12 times |
| Tutorial/Workshop 1 – Scheduled online workshops (Recorded). | 2hrs | Week 1 | 12 times |
Introduction to the linear regression model and using a statistical package
Functional forms of regression models
Qualitative vs quantitative explanatory variables
Multicollinearity, heteroscedasticity, autocorrelation, and specification errors
The logit and probit models
Panel regression models
Stationarity and cointegration
300 Level (Graduate)
12 units
| Course Learning Outcomes On successful completion of this course, you should be able to... | Graduate Qualities Mapping Completing these tasks successfully will contribute to you becoming... | Professional Standard Mapping * Competencies from multiple Professional Bodies (see below) * | |
| 1 | Frame problems in terms of core economic concepts using the fundamentals tools of econometrics and their application to testing economic theories. |
Knowledgeable Creative and critical thinker Empowered |
PC1.1, PC1.3, PC3.1, PC6.2 |
| 2 | Implement basic empirical techniques and interpret the results using a standard statistical package to analyse various types of economic problems. |
Knowledgeable Creative and critical thinker Empowered |
PC1.1, PC1.3, PC3.1, PC6.2 |
| 3 | Use appropriate economic data and statistical methods to conduct independent econometric analysis, as well as present a clear and coherent exposition and appraise the outcome of that analysis. |
Knowledgeable Creative and critical thinker Empowered |
PC1.1, PC3, 5.3.4, 5.3.5, PC6 |
| CODE | COMPETENCY |
| Association to Advance Collegiate Schools of Business | |
| PC1.1 | Written Communication |
| PC1.3 | Digital Literacy |
| PC3 | Creative and Critical Thinking |
| PC3.1 | Problem Solving |
| PC6 | Career-ready |
| PC6.2 | Discipline Knowledge |
| Education for Sustainable Development Goals | |
| 5.3.4 | The learner is able to observe and identify gender discrimination. |
| 5.3.5 | The learner is able to plan, implement, support and evaluate strategies for gender equality. |
Refer to the UniSC Glossary of terms for definitions of “pre-requisites, co-requisites and anti-requisites”.
BUS201 or BUS202
Not applicable
Not applicable
Not applicable
Not applicable
Standard Grading (GRD)
| High Distinction (HD), Distinction (DN), Credit (CR), Pass (PS), Fail (FL). |
Hands-on exercises in using statistical software will start in Week 1 with feedback provided orally in class and in written form by means of model programs and results supplied on Canvas.
| Delivery mode | Task No. | Assessment Product | Individual or Group | Weighting % | What is the duration / length? | When should I submit? | Where should I submit it? |
| All | 1 | Written Piece | Individual | 50% | 1500 words |
Week 7 | Online Assignment Submission with plagiarism check |
| All | 2 | Report | Individual | 50% | 1500 words (excluding graphs, tables and references) |
Week 12 | Online Assignment Submission with plagiarism check |
| All - Assessment Task 1:Problem set | ||||||||||||||||
| Goal: | To use statistical software to summarise and interpret both descriptive and basic inferential statistics, and to apply and analyse the findings from a range of econometric models. |
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| Product: | Written Piece | |||||||||||||||
| Authorship Statement: | ||||||||||||||||
| Format: | Work must be completed individually. Written answers should summarise key information using tables and/or graphs generated with statistical software, supported by a clear and concise written explanation. Further details are provided in the assessment area on Canvas. |
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| Criteria: |
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| Generic Skills: | Communication, Problem solving, Applying technologies, Information literacy |
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| All - Assessment Task 2:Applied project | |||||||||||||
| Goal: | To present a clear and coherent exposition of ideas and empirical evidence by completing an applied project using an econometrics software package. |
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| Product: | Report | ||||||||||||
| Authorship Statement: | |||||||||||||
| Format: | The report will include a justification of the methods chosen, interpretation and analysis of the empirical results and discussion of limitations. Focus will be on methods from later parts of the course. Further details are provided in the assessment area in Canvas. |
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| Criteria: |
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| Generic Skills: | Communication, Problem solving, Organisation, Applying technologies, Information literacy |
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| Programme Delivery Mode | Assessment Type | Title | Competency | Teaching Methods |
|---|---|---|---|---|
| 2020 UniSC Business School Standards Undergraduate | ||||
| All delivery modes | Report | Applied project | PC1.1 | Assessed |
| PC1.3 | Taught, Practiced, Assessed | |||
| PC3.1 | Taught, Practiced, Assessed | |||
| PC6.2 | Taught, Practiced, Assessed | |||
| Written Piece | Problem set | PC1.1 | Assessed | |
| PC1.3 | Taught, Practiced, Assessed | |||
| PC3.1 | Taught, Practiced, Assessed | |||
| PC6.2 | Taught, Practiced, Assessed | |||
A 12-unit course will have total of 150 learning hours which will include directed study hours (including online if required), self-directed learning and completion of assessable tasks. Student workload is calculated at 12.5 learning hours per one unit.
Please note: Course information, including specific information of recommended readings, learning activities, resources, weekly readings, etc. are available on the course Canvas site– Please log in as soon as possible.
You need regular access to the resource(s) below. Many texts are available as ebooks through the Library at no additional cost.
| Required? | Author | Year | Title | Edition | Publisher |
| Recommended | Damodar Gujarati | 2017 | Econometrics by Example | 2nd | Bloomsbury Publishing |
Access to a computer. Student version of an econometric software package (available for free download).
Academic integrity is the ethical standard of university participation. It ensures that students graduate as a result of proving they are competent in their discipline. This is integral in maintaining the value of academic qualifications. Each industry has expectations and standards of the skills and knowledge within that discipline and these are reflected in assessment.
Academic integrity means that you do not engage in any activity that is considered to be academic fraud; including plagiarism, collusion or outsourcing any part of any assessment item to any other person. You are expected to be honest and ethical by completing all work yourself and indicating in your work which ideas and information were developed by you and which were taken from others. You cannot provide your assessment work to others. You are also expected to provide evidence of wide and critical reading, usually by using appropriate academic references.
In order to minimise incidents of academic fraud, this course may require that some of its assessment tasks, when submitted to Canvas, are electronically checked through Turnitin. This software allows for text comparisons to be made between your submitted assessment item and all other work to which Turnitin has access.
Eligibility for Supplementary Assessment
Your eligibility for supplementary assessment in a course is dependent of the following conditions applying:
(a) The final mark is in the percentage range 47% to 49.4%; and
(b) The course is graded using the Standard Grading scale
Late submissions may be penalised up to and including the following maximum percentage of the assessment task’s identified value, with weekdays and weekends included in the calculation of days late:
(a) One day: deduct 5%;
(b) Two days: deduct 10%;
(c) Three days: deduct 20%;
(d) Four days: deduct 40%;
(e) Five days: deduct 60%;
(f) Six days: deduct 80%;
(g) Seven days: A result of zero is awarded for the assessment task.
The following penalties will apply for a late submission for an online examination:
Less than 15 minutes: No penalty
From 15 minutes to 30 minutes: 20% penalty
More than 30 minutes: 100% penalty
For more information on Academic Learning & Teaching categories including:
For more information, visit https://www.usc.edu.au/explore/policies-and-procedures#academic-learning-and-teaching
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