Regression Modelling G (6557.4)

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.
This unit may be cotaught with 6546 Regression Modelling.

Learning outcomes

On 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;

6. Interpret the results of an estimated model and predict the consequences of these results;

7. Produce the results of analyses in a form which is suitable for publication; and

8. Apply important extensions to the linear regression model.

Graduate attributes

1. UC graduates are professional - communicate effectively
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - take pride in their professional and personal integrity
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - evaluate and adopt new technology

Prerequisites

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

Corequisites

None.

Incompatible units

6546 Regression Modelling.

Equivalent units

None.

Assumed knowledge

None.