Year
2024Credit points
10Campus offering
Prerequisites
NilIncompatible
PUBH620 Biostatistics , HLSC647 Quantitative Research Methods
Unit rationale, description and aim
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.
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.
| Learning Outcome Number | Learning Outcome Description | Relevant Graduate Capabilities |
|---|---|---|
| LO1 | Identify appropriate statistical techniques and their application to health science research and practice | GC1, GC2, GC8 |
| LO2 | Distinguish between different statistical tests, especially in terms of application and interpretation | GC1, GC2, GC8 |
| LO3 | Perform appropriate statistical analysis using common statistical software and interpret the results | GC1, GC2, GC7, GC8, GC10 |
| LO4 | Develop a sound statistical approach to the analysis and interpretation of health science data and communicate findings in an academic-standard output | GC1, GC2, GC7, GC9, GC11 |
| LO5 | Critique health science research on the basis of its statistical methods, analysis and interpretation | GC1, GC2, GC7, GC9, GC11 |
Content
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
Learning and teaching strategy and rationale
In online mode, students acquire essential theoretical knowledge in biostatistics via a series of synchronous or asynchronous online lessons which include: video content, online readings, online discussion forums and self-directed learning modules. Facilitated synchronous or asynchronous online classes will be used to aid students in the construction and synthesis of this knowledge using expert led and peer-to-peer strategies to develop students' ability to apply biostatistics principles and approaches to contemporary health science issues.
This unit uses an active learning approach to support students in the exploration of knowledge essential to the discipline. Students are provided with choice and variety in how they learn. Students are encouraged to contribute to asynchronous weekly discussions. Active learning opportunities provide students with opportunities to practice and apply their learning in situations similar to their future professions. Activities encourage students to bring their own examples to demonstrate understanding and application, and to engage constructively with their peers. Students receive regular and timely feedback on their learning, which includes information on their progress.
Assessment strategy and rationale
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.
Overview of assessments
| Brief Description of Kind and Purpose of Assessment Tasks | Weighting | Learning Outcomes |
|---|---|---|
Assessment Task 1: Analysis of simulated public health dataset. This task will enable students to develop an understanding of data analysis by analysing a health science data set. | 20% | LO1, LO2, LO3, LO4 |
Assessment Task 2: Preparation of statistical methods and analysis for a peer-reviewed journal article. This task will enable students to deepen their knowledge of data analysis by writing the methods and data analysis sections of a journal article. | 40% | LO2, LO3, LO4, LO5 |
Assessment Task 3: Biostatistics reflective practice and critique exercises. This task will enable students to demonstrate their understanding of biostatistical practice through critique of published research and reflect upon their learning in the unit and how they relate to competency standards for health science research and practice. | 40% | LO1, LO5 |
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.
Bland, M. (2015). An introduction to medical statistics (4th ed.). Oxford University Press.
Field, A. P. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.
Moore, D. S., Notz, W., & Fligner, M. A. (2018). The basic practice of statistics (Eighth edition.). New York, NY: Macmillan Education.
Newell, R., & Burnard, P. (2011). Research for evidence-based practice in health care (2nd ed.). Chichester, England: Wiley-Blackwell.
Pallant, J. F. (2016). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (6th ed.). Crows Nest: Allen & Unwin.
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.
Wagner, W. E., & Gillespie, B. J. (2019). Using and interpreting statistics in the social, behavioral, and health sciences. SAGE Publications, Inc.