- Code POPH8313
- 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 Public 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.
Data analysis is a central activity in applied epidemiology providing underlying evidence for public health policy formulation and action. Data may come from studies with survey, cohort or case control designs, or from health system surveillance or monitoring. The different types of data require different analytic methods appropriate to the form of the data and to the research question. This course aims to introduce students to some different types of quantitative public health data, with a focus on secondary dataset analysis, and to give students the opportunity for hands-on learning of epidemiological data analysis skills. The course is relevant to any student interested in a career in public health or health research, or to those wishing to extend their statistical skills to analysis of public health data.
Upon successful completion, students will have the knowledge and skills to:
- Define questions of public health significance appropriate to secondary dataset analysis
- Design an analysis plan
- Perform a descriptive analysis
- Identify and use appropriate statistical analytic approaches and methods
- Identify limitations of data analyses
- Communicate findings for public health action
Students enrolled in this course should have completed an undergraduate degree and Masters level courses on Epidemiology and/or Biostatistics from a recognised School
of Public Health (either in Australia or internationally), or completion of POPH8100 Fundamentals of Epidemiology and POPH8101 Biostatistics in Population Health courses held at the ANU, or equivalent experience. Students wishing to do this subject, but do not have these prerequisites should contact the convener.
- Online quiz (40) [LO 3,4]
- Written assignment (statistical analysis plan) (20) [LO 1,2]
- Written assignment (statistical analysis report) (40) [LO 3,4,5,6]
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This course can be taken either fully online, or in person. The expected workload will consist of approximately 130 hours throughout the semester, which will include:
On-line delivery: Online students will engage with the material throughout the semester and will receive the same level of support via email and online mechanisms.
In person delivery: Students who choose to take this course in person are expected to attend lectures (2-3 hours per week face-to-face sessions) including self directed study which will include preparation for assignments.
Prior to the start of Semester all students must complete an introductory online non-assessable quiz.
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.
Betty Kirkwood & Jonathon Stern. Essential Medical Statistics. 3rd Edition. Blackwell Science, Oxford 2012. ISBN: 1405158964
Understanding of basic epidemiology and biostatistics.
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.
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Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.