- Code POPH4101
- Unit Value 6 units
- Offered by Research School of Population Health
- ANU College ANU Joint Colleges of Science
- Course subject Population Health
- Areas of interest Population Studies, Public Health, Health
This course is offered in two modes: online and in person. Please select the correct class number for the relevant mode of delivery when enrolling.
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 specialised 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
Throughout the course, the emphasis will be on understanding the reasons why the techniques are appropriate, underlying assumptions, use of the statistical analysis package Stata and interpretation of results, rather than the mechanics of calculation. Each topic will draw upon one or two papers from the literature. Both online materials and drop-in help sessions in a computer lab will be used to facilitate learning and provide opportunities to explore specific topics in more detail.
Upon successful completion, students will have the knowledge and skills to:
- Define and explain mathematical and biostatistical concepts covered in the course.
- Produce appropriate visual displays and summary statistics for datasets, and describe the shape and properties of the data from those outputs.
- Choose and implement appropriate statistical models and tests and interpret their outputs to make inferences from data; continuous outcomes, binary data, categorical data, survival data.
- Produce appropriate diagnostic plots for statistical models and use these to critically assess the assumptions of the model against the data.
- Construct functioning scripted statistical analysis (in STATA or R) to load, wrangle, and analyse a dataset.
- Critically assess the statistical methods and evidence presented in published research studies.
- Online quizzes (10) [LO 1,2,3]
- Assignment 1 (30) [LO 1,2,3,6]
- Assignment 2 (35) [LO 1,2,3,6]
- Take home exam (5) [LO 1,2,3,4,5,6]
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In Person delivery mode: weekly computer laboratory, online lectures 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
To be determined
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 TextsBetty R Kirkwood & Jonathan AC Sterne. Essential Medical Statistics (2nd Ed). Oxford: Blackwell Science Ltd, 2003. ISBN-13: 978-0865428713
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
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.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|3222||20 Feb 2023||27 Feb 2023||31 Mar 2023||26 May 2023||In Person||N/A|
|2876||20 Feb 2023||27 Feb 2023||31 Mar 2023||26 May 2023||Online||N/A|