Unit rationale, description and aim
Understanding, using and interpreting biostatistical and epidemiological data is crucial to public health research and practice, particularly in monitoring health outcomes and decision-making processes about interventions. This unit will develop students' knowledge of advanced biostatistical and epidemiological concepts used in public health. Key biostatistical concepts will include statistical inference, measures of association and evidence-based metrics as well as the use of statistical software and critical appraisal of statistical methods. Students will use statistical software to analyse simulated public health data sets and then interpret the results obtained. Key epidemiological concepts will be screening and diagnostic test evaluation, and specialised epidemiology including social, behavioural, clinical and infectious disease epidemiology. The measurement of heterogeneity and meta-analysis in systematic reviews of health interventions will be covered. Emphasis will be placed on the application of biostatistics and epidemiology in public health practice. Throughout the unit, students will consolidate their understanding of biostatistical and epidemiological theory through its application to practice. The aim of this unit is to develop students' knowledge of advanced biostatistical and epidemiological concepts and analytical expertise for application in public health practice.
Campus offering
No unit offerings are currently available for this unit.Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
Describe and apply advanced biostatistics and epid...
Learning Outcome 01
Demonstrate proficiency in the use of statistical ...
Learning Outcome 02
Apply epidemiological techniques such as screening...
Learning Outcome 03
Critically examine how epidemiology is applied in ...
Learning Outcome 04
Content
Topics will include:
Advanced biostatistics in public health
- Key measures of association (e.g. relative risk, attributable risk, odds ratios)
- Inferential statistics: linear regression, logistic regression, analysis of variance
- Use of statistical software to analyse quantitative datasets using common statistical tests
- Evidence-based practice (e.g. numbers needed to treat/harm)
- Interpretation of statistical analyses in public health research
Advanced epidemiology in public health
- Disease prevention and treatment: screening and diagnostic test evaluation
- Specialised epidemiology: social, behavioural, clinical and infectious disease
- Systematic reviews of health interventions: heterogeneity, meta-analysis
Practical epidemiology
- Application of epidemiology in public health practice: role in needs assessment, impact evaluation and health policy
- Health protection: monitoring and surveillance, notifiable diseases and legislative requirements
- Investigation of an epidemic: contact tracing and mandatory notification
- The role of the Australian Centre for Disease Control: disease surveillance functions, statements and advice, publications and resources
Assessment strategy and rationale
Assessment in this unit will comprise three assessment tasks, combining written and oral activities. The assessment strategy allows students to progressively develop their knowledge and skills by first understanding key concepts that underpin biostatistics and epidemiology, then applying this knowledge by analysing a simulated data set, and then making an interactive oral presentation on an application of advanced epidemiology.
The first assessment task requires students to address key concepts in biostatistics and epidemiology including statistical inference; power and sample size; bias, confounding and adjustment, measures of association and metrics used in evidence-based practice and inferential statistics.
The second assessment task, building on the first, is a written assessment which requires students to perform a written analysis of a simulated data set using common statistical tests,
The third assessment task requires students to make an interactive oral presentation of the application of advanced epidemiology in public health practice such as disease prevention, specialised epidemiology or the application of epidemiology in public health practice (e.g. needs assessment, impact evaluation or health policy).
To pass the unit, students must demonstrate achievement of every unit learning outcome and obtain a minimum mark of 50% in this unit.
Overview of assessments
Assessment 1:Written assessment To provide short...
Assessment 1:Written assessment
To provide short answers to questions, on topics drawn from weeks one to three, that will enable students to describe key concepts (800 words)
20%
Assessment 2: Written assessment To perform a wr...
Assessment 2: Written assessment
To perform a written analysis of a simulated data set demonstrating advanced statistical skills. (1,500 words)
40%
To make an interactive oral presentation on an ap...
To make an interactive oral presentation on an application of advanced epidemiology in public health practice (15 mins)
40%
Learning and teaching strategy and rationale
Teaching and learning strategies addressing basic concepts and frameworks will involve lectures, tutorials, small group discussions and interactive asynchronous sessions using LMS. Specialised topics will rely on videos, discussions with experts in various settings, and use of case studies.
The design of this unit is based on the constructivist approach, which supports active learning that encourages students to engage in a range of learning activities to facilitate the construction of new knowledge. Constructive alignment is achieved between learning outcomes, content and assessment tasks.
Representative texts and references
Barton, B., & Peat, J. K. (2014). Medical statistics : a guide to SPSS, data analysis, and critical appraisal (2nd ed.). Wiley-Blackwell.
Bush, H. M. (2012). Biostatistics: An applied introduction for the public health practitioner. Clifton Park, NY: Delmar Cengage Learning.
Goodman, M.S (2026) Biostatistics for Clinical and Public Health Research (2nd edition). Routledge
Gordis, L., & Forgione, L. (2019). Epidemiology (6th ed.). Elsevier.
National Statement on Ethical Conduct in Human Research 2007 (updated 2018) The National Health and Medical Research Council, the Australian Research Council and the Australian Vice-Chancellors’ Committee. Commonwealth of Australia Canberra. Available for download from: https://www.nhmrc.gov.au/guidelines-publications/e72
Pallant, J. F. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). Taylor and Francis Group.
Portney, L. G. (2020). Foundations of clinical research: Applications to practice (4th ed.). F. A. Davis
Rowntree, D. (2018). Statistics Without Tears: An Introduction For Non-Mathematicians (1st ed.) Penguin Press.
von Elm, E. & Egger, M. (2004). The scandal of poor epidemiological research: Reporting guidelines are needed for observational epidemiology. British Medical Journal, 329(7471), 868-869. doi: 10.1136/bmj.329.7471.868.
Wagner, W. E., & Gillespie, B. J. (2019). Using and interpreting statistics in the social, behavioral, and health sciences. SAGE Publications, Inc.
Webb, P. & Bain, C. (2017). Essential epidemiology: An Introduction for students and health professionals (3rd ed.). Cambridge University Press [ACU ebook].