Postgraduate | ACU-HLSC642 | 2023
Biostatistics for Health Sciences
Explore fundamental statistical concepts and use common statistics software. You’ll learn how statistics are used in health science research and practice. Gain skills to interpret health-related data. Make confident decisions based on evidence.
- Study method
- 100% online
- 100% online
- Entry requirements
- Part of a degree
- 10 weeks
- 09 Oct 2023
About this subject
On successful completion of this unit, students should be able to:
- LO1 - Identify appropriate statistical techniques and their application to health science research and practice (GA5)
- LO2 - Distinguish between different statistical tests, especially in terms of application and interpretation (GA4, GA5, GA6)
- LO3 - Perform appropriate statistical analysis using common statistical software and interpret the results (GA6, GA8)
- LO4 - Develop a sound statistical approach to the analysis and interpretation of health science data and communicate findings in an academic-standard output (GA4, GA8)
- Topics will include:
- - Fundamental statistical concepts and methods
- Types and levels of measurement of quantitative data and measures of central tendency and variability
- Probability distributions
- Hypothesis testing
- Statistical confidence: confidence intervals, p-values, statistical effect sizes
- Common statistical tests: comparison of means (between two or more dependent or independent groups), proportions
- Variability and statistical inference;
- - Application to health science practice
- Key measures of association in health sciences: relative risk, attributable risk, odds ratios
- Inferential statistics: correlation, linear regression, logistic regression, analysis of variance
- Use of statistical software to analyse quantitative data sets: common statistical tests
- Writing up statistical analyses: interpretation, requirements for expressing statistical results
- Critical appraisal of statistical methods in health sciences research: common tools and approaches
Understanding, using and interpreting statistics is crucial to health science research and practice, particularly in monitoring health outcomes and decision-making processes about interventions. This unit will develop students' knowledge of fundamental statistical concepts, such as descriptive and inferential statistics, common statistical tests and statistical methods frequently used in health science research. This will include hypothesis testing, estimation, associations, modelling relationships and prediction using different methods such as regression analyses. Throughout the unit, students will consolidate their understanding of statistical theory through its application to practice. While there are some formulae and computational elements to the unit, the emphasis is on interpretation and concepts. Besides the theoretical material, this unit will also enable students to run basic analyses using common statistical software. Using this software, students will analyse simulated health science data sets and then interpret the results obtained. This unit aims to extend students' statistical understanding and analytical expertise, which can then be applied to practice through critical appraisal statistical methods used in health science research.
A range of assessment procedures will be used to meet the unit learning outcomes and develop graduate attributes consistent with University assessment requirements. In order to successfully complete this unit, students need to complete and submit three graded assessment tasks and obtain an aggregate mark of greater than 50%.
Assessment tasks for this unit have been designed to introduce students to the broad range of activity involved in biostatistics. In Assessment Task 1, students are required to demonstrate their understanding by analysing a health science data set. In Assessment Task 2, students are required to apply their biostatistical skills by preparing statistical methods and analysis for a peer reviewed journal article. Finally, in Assessment Task 3 students will critique and interpret the statistics in current published journal articles and reflect on how biostatistical knowledge will shape their professional practice.
- Analysis of simulated public data set - 2 parts (20%)
- Preparation of statistical methods and analysis for a peer-reviewed journal article. (40%)
- Biostatistics reflective practice and critique exercises (40%)
For textbook details check your university's handbook, website or learning management system (LMS).
Established in 1991 after amalgamating four eastern Australian Catholic tertiary institutes, Australian Catholic University now has seven campuses, from Brisbane to Melbourne and welcomes students of all beliefs. Specialising in arts, business, education, health sciences, law, theology and philosophy, ACU encourages its students to think critically and ethically and bring change to their communities and offer this online through Open Universities Australia.
Learn more about ACU.
Explore ACU courses.
- QS Ranking 2023:
- Times Higher Education Ranking 2023:
To enrol in this subject, you must be admitted into a degree.
You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
- Software requirements - SPSS offered at a reduced cost to ACU students.
This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.