Regression Modelling (6546.4)
|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 2020 Semester 2 DR Shuangzhe LIU (Ph: +61 2 62012513 ) ON-CAMPUS
Possible changes to your unit's learning activities and assessment items
As a result of the Australian 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.
New learning activities and/or assessment items are available on your unit's UCLearn(Canvas) teaching site. Please contact your Unit Convener with any questions.
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 1, 2019, ON-CAMPUS, BRUCE (185231) - View
- Semester 1, 2018, ON-CAMPUS, BRUCE (181705) - View
- Semester 2, 2016, ON-CAMPUS, BRUCE (151538) - 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 explores linear regression techniques for examining relationships between a variety of variables, including both continuous and discrete response variables. Emphasis will be placed on the practical aspects of analysing large data sets, fitting a model and assessing a model using a statistical package. The simple regression model will be reviewed. Multiple regression models will be introduced, together with logistic regression and other generalised linear models. Applications to business, natural and social sciences and other areas will be illustrated.
On successful completion of this unit, students will be able to:
1. Describe the principles of linear modelling in data analysis;
2. Formulate an appropriate model;
3. Estimate the parameters of a model using a statistical computer package;
4. Apply and explain statistical inference to a model using a statistical computer package;
5. Evaluate the appropriateness and validity of a model; and
6. Produce and interpret the results of an estimated model and predict the consequences of these results.
A 2-hour lecture and a 2-hour lab per week.
6540 Introduction to Statistics OR 5123 Business Statistics OR 1809 Data Analysis in Science
- 986AA Bachelor of Arts / Bachelor of Advertising and Marketing Communication
- 987AA Bachelor of Arts / Bachelor of Journalism
- 988AA Bachelor of Arts / Bachelor of Media Arts and Production
- 989AA Bachelor of Arts / Bachelor of Public Relations
- 798AA Bachelor of Arts/Bachelor of Commerce
- 125JA Bachelor of Arts/Bachelor of Communication and Media Studies
- 216JA Bachelor of Arts/Bachelor of Communication in Advertising
- 217JA Bachelor of Arts/Bachelor of Communication in Journalism
- 218JA Bachelor of Arts/Bachelor of Communication in Media and Public Affairs
- 219JA Bachelor of Arts/Bachelor of Communication in Public Relations
- 799AA Bachelor of Arts/Bachelor of Information Technology
- 801AA Bachelor of Arts/Bachelor of Laws
- 802AA Bachelor of Arts/Bachelor of Management
- 804AA Bachelor of Arts/Bachelor of Science in Psychology
- 392AB Bachelor of Science
- 994AA Bachelor of Science / Bachelor of Journalism
- NPSC01 Bachelor of Science/ Bachelor of Laws
- 836AA Bachelor of Science/Bachelor of Laws