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Foundations of Regression (MAST90102)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable (login required)(opens in new window)
Contact information
July
emily.karahalios@unimelb.edu.au
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Overview
| Availability | July - Dual-Delivery |
|---|---|
| Fees | Look up fees |
This subject provides the foundation for understanding and using regression methods in biostatistics. Students will learn what a regression model is and how regression methods are used for the major purposes of research investigations: description, prediction and causal inference. The emphasis will be on learning how to build, fit and interpret regression models for these different purposes, focusing on linear regression for continuous outcomes and logistic regression for binary outcomes, and including treatment of key issues such as model fit, parametrisation and interaction. Important underlying mathematical concepts will be covered, such as the method of least squares, maximum likelihood estimation and matrix algebra representation of multiple regression.
Intended learning outcomes
On completion of this subject, students should be able to:
- Explain the concepts of regression models for continuous and binary outcomes as tools for description, prediction, and causal inference in health research, including the required assumptions.
- Interpret the parameters of regression models for describing variation in continuous outcomes (linear regression) and binary outcomes (logistic regression).
- Explain the key principles involved in building and validating regression models for prediction purposes.
- Use multivariable regression models to estimate causal effects such as mean difference, risk difference, risk ratio, odds ratio, including the required causal and parametric assumptions.
- Use statistical software to fit regression models for each of the specified purposes to datasets with continuous and binary outcomes.
Generic skills
- Independent problem solving
- Facility with abstract reasoning
- Clarity of written expression
- Sound communication of technical concepts
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
All of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST90100 | Probability & Inference in Biostatistics | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
| POPH90014 | Epidemiology 1 |
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Dual-Delivery - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
| Description | Timing | Percentage |
|---|---|---|
Practical Exercise 1
| Week 2 | 20% |
Major Assignment 1
| Week 4 | 40% |
Major Assignment 2
| 1 Weeks after the end of teaching | 40% |
Last updated: 31 January 2024
Dates & times
- July
Coordinator Emily Karahalios Mode of delivery Dual-Delivery (Parkville) Contact hours Total time commitment 170 hours Teaching period 22 July 2024 to 30 August 2024 Last self-enrol date 30 July 2024 Census date 2 August 2024 Last date to withdraw without fail 23 August 2024 Assessment period ends 13 September 2024 July contact information
emily.karahalios@unimelb.edu.au
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: https://study.unimelb.edu.au/
Time commitment details
170 hours
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
Resources Provided to Students online: Course notes and assignments.
Special Computer Requirements: Stata statistical software. - Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Diploma in Biostatistics Course Master of Biostatistics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024