This course will examine principles of biostatistics, in the context of real-world public health issues. The aim of the course is to help those without a technical background to read and interpret biostatistical content in the medical and public health literature.
Topics, chosen by frequency of occurrence in the literature, will include:
- Introduction to sampling distributions, hypothesis tests and estimation
- Analysis of normal data, including t-tests and linear regression
- Analysis of binary data, including 2x2 tables, Mantel-Haenszel methods and logistic regression
- Analysis of count data, including comparing rates between two groups,
- Poisson regression and survival analysis
Throughout the course, the emphasis will be on understanding the reasons why the techniques are appropriate, underlying assumptions and interpretation of results, rather than the mechanics of calculation. Each topic will draw upon one or two papers from the literature. Both lectures and computer laboratories will be used to facilitate learning and provide opportunities to explore specific topics in more detail.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Upon successful completion of this course, students will have the knowledge and skills to:
1. Explain the various mathematical and biostatistical concepts covered during the course
Recognize differences in data distributions via visual displays
2. Give examples of different types of data and know the appropriate techniques for analysing: continuous outcomes; binary data; count data; and survival data
3. Interpret the results of: t-tests and linear regression; 2x2 tables, Mantel-Haenszel methods and logistic regression; Poisson regression; Cox regression; and meta-analysis
4. Critically appraise the evidence presented in published research studies
Indicative Assessment
Assignments 60%take-home exam 35%
Quiz 5%
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
In Person delivery mode: online lectures and weekly computer laboratory, plus 7 hours per week of associated study.
Online delivery mode: 10 hours per week of reading, online lessons, exercises and assessment preparation
Please note: the course is offered in both In Person and Online mode in Semester 1, and in Online mode only in Semester 2
Requisite and Incompatibility
You will need to contact the Research School of Population Health to request a permission code to enrol in this course.
Prescribed Texts
Betty R Kirkwood & Jonathan AC Sterne. Essential Medical Statistics (2nd Ed). Oxford: Blackwell Science Ltd, 2003. ISBN-13: 978-0865428713Fees
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2019 | $4260 |
- International fee paying students
| Year | Fee |
|---|---|
| 2019 | $6060 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 3730 | 25 Feb 2019 | 04 Mar 2019 | 31 Mar 2019 | 31 May 2019 | In Person | View |
| 4287 | 25 Feb 2019 | 04 Mar 2019 | 31 Mar 2019 | 31 May 2019 | Online | View |
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 8756 | 22 Jul 2019 | 29 Jul 2019 | 31 Aug 2019 | 25 Oct 2019 | Online | View |