|Level:||Level 3 - Undergraduate Advanced Unit|
|HECS Bands:||2, 4|
|Faculty:||Faculty of Science and Technology|
|Discipline:||Academic Program Area - Technology|
UC - Canberra, Bruce
Year Teaching Period Convener Mode of Delivery 2021 Semester 2 DR Shuangzhe LIU (Ph: +61 2 62012513 ) FLEXIBLE
Possible changes to your unit's learning activities and assessment items
For the remainder of 2020, resulting from Australian Government's directives requiring physical distancing and restrictions on movement because of the COVID-19 pandemic, any exams that are required for assessment in a unit will be online exams. Online exams may also use online proctoring to help assure the academic integrity of those exams. Please contact your unit convener with any questions.
While the University has made efforts to ensure that Unit Outlines reflect a unit’s learning activities and assessment items, any changes to Australian Government directives because of the COVID-19 pandemic may require changes to these during the semester to ensure the safety and well being of students and staff. 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. Any changes made will continue to meet the unit’s learning outcomes, as described in the Unit Outline.
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- Semester 2, 2019, FLEXIBLE, BRUCE (185527) - View
- Semester 2, 2018, FLEXIBLE, BRUCE (181699) - View
- Semester 2, 2017, FLEXIBLE, BRUCE (169994) - View
- Semester 1, 2016, ON-CAMPUS, BRUCE (155012) - View
- Semester 1, 2015, ON-CAMPUS, BRUCE (145706) - View
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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.
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; and
6. Produce and interpret the results of analyses.
A 2-hour lecture and a 2-hour lab per week.
5123 Business Statistics OR 1809 Data Analysis in Science OR 6540 Introduction to Statistics
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