Unit rationale, description and aim
Understanding, using and interpreting statistics is crucial to biomedical and health sciences 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 biomedical and health sciences 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 of the statistical methods used in biomedical and health sciences 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.
Perform appropriate statistical tests relevant to ...
Learning Outcome 01
Report statistical procedures, outcomes, and their...
Learning Outcome 02
Critique biomedical and health science research on...
Learning Outcome 03
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 significance, effect sizes
- Common statistical tests: comparison of means (between two or more dependent or independent groups), proportions
- Parametric vs. non-parametric tests
- Variability and statistical inference; power and sample size; sampling bias
Application to scientific research practice:
- Key measures of association: relative risk, absolute risk, odds ratio
- Inferential statistics: correlation, linear regression, analysis of variance
- Use of statistical software to analyse quantitative datasets
- Writing up statistical analyses: interpretation, requirements for expressing statistical results
- Critical appraisal of statistical methods in scientific research
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, demonstrate achievement of every unit learning outcome and obtain a minimum mark of 50% in the unit.
This unit involves assessment tasks designed to introduce students to the broad range of activities involved in health statistics. In Assessment Task 1, students are required to demonstrate their ability to conduct basic statistical procedures and data visualisations using statistical software by analysing a health science dataset. In Assessment Task 2, students will analyse a provided health science dataset and report the statistical procedures, results, and interpretation for a peer-reviewed journal article. Finally, in Assessment Task 3 (a graded hurdle task), students will critique and interpret the statistics in current published journal articles/available datasets and use their statistical knowledge to inform a statistical methods research plan for their Honours projects.
Students will be allowed one re-attempt at the graded hurdle task (i.e., Assessment Task 3).
In order to pass the unit, students must demonstrate achievement of every unit learning outcome, pass the hurdle task and obtain a minimum cumulative mark of 50%. All assessments will be submitted electronically.
Overview of assessments
Assessment task 1: Analysis of simulated healt...
Assessment task 1: Analysis of simulated health science-related dataset. This will enable students to develop an understanding of data analysis and its application.
20%
Assessment task 2: Preparation of statistical ...
Assessment task 2: Preparation of statistical methods and analysis for a peer-reviewed journal article.
This will enable students to deepen their knowledge of data analysis by writing the statistical methods, results and discussion sections of a mock journal article.
40%
Assessment task 3 (graded hurdle): Statistical m...
Assessment task 3 (graded hurdle): Statistical methods comprehension assignment. This will enable students to demonstrate that they comprehend the appropriate statistical tests/techniques to reflect unit content. This will better prepare them for their Honours project.
40%
Learning and teaching strategy and rationale
Online mode
Students acquire essential theoretical knowledge in biostatistics via a series of synchronous or asynchronous online lessons which include recorded lecture content, online readings, online discussion forums and self-directed learning modules. Facilitated synchronous or asynchronous online tutorial classes (virtual classroom) 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’ abilities to apply biostatistics principles and approaches to contemporary biomedical and health science issues.