Useful links
The aim of this unit is to lay the foundation of biostatistical modelling to analyse data from randomised or observational studies. These skills are essential for biostatistics in practice and will be used by students for the remainder of their Master of Biostatistics studies. This unit will introduce the motivation for different regression analyses and how to choose an appropriate modelling strategy. This unit will teach how to use linear regression to analyse continuous outcomes and logistic regression for binary outcomes. Emphasis will be placed on interpretation of results and checking the model assumptions. Stata and R software will be used to apply the methods to real study datasets.
Study level | Postgraduate |
---|---|
Academic unit | Public Health |
Credit points | 6 |
Prerequisites:
?
|
(BSTA5011 or PUBH5010 or CEPI5100) |
---|---|
Corequisites:
?
|
BSTA5002 |
Prohibitions:
?
|
BSTA5007 or BSTA5008 |
Assumed knowledge:
?
|
None |
At the completion of this unit, you should be able to:
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
Session | MoA ? | Location | Outline ? |
---|---|---|---|
Semester 1 2024
|
Online | Camperdown/Darlington, Sydney |
View
|
Semester 2 2024
|
Online | Camperdown/Darlington, Sydney |
View
|
Session | MoA ? | Location | Outline ? |
---|---|---|---|
Semester 1 2025
|
Online | Camperdown/Darlington, Sydney |
Outline unavailable
|
Semester 2 2025
|
Online | Camperdown/Darlington, Sydney |
Outline unavailable
|
Find your current year census dates
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.