BMSC100 - Introductory Biostatistics

Year

Credit points

Campus offering

Prerequisites

Teaching organisation

Unit rationale, description and aim

The ability to describe, manage, analyse and interpret data is crucial to the practice of science. Therefore, it is important for biomedical scientists to understand and competently use statistical techniques and to be able to draw valid conclusions from statistical analyses. In this unit, students will learn to describe, manage, summarise, and present data. They will be introduced to the most commonly encountered types of variables, learn how to recognise and apply appropriate statistical tests, and learn to interpret and effectively communicate the results. Students will gain foundational knowledge of statistical models used in biomedical science and develop skills to implement such models by hand and using statistical software. The aim of this unit is to help students to develop the understanding and skills needed to recognise and apply appropriate statistical tools. 

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.

Content

Topics will include: 

• Exploring data with graphs
• Summarising data using descriptive statistics 
• Sampling bias
• Using software for statistical analyses 
• Hypothesis testing 
• Comparing averages
• Correlation and linear regression 
• Parametric versus non-parametric models
• Measures of association

Learning and teaching strategy and rationale

Biomedical scientists need to be able to use, interpret and draw conclusions from statistical analyses and communicate their findings to others. Acquiring these skill requires active involvement in solving statistical problems and applying the knowledge gained. This unit fosters student-centred active learning and accommodates diverse student needs. Classes focus on practice in applying statistical concepts and techniques, and learning to interpret and communicate statistical output in a standardised way. The unit is structured to progressively build knowledge week by week. Early feedback on learning, and tailored support, are provided to facilitate students’ transition to university. The progressive learning approach is supported by a series of weekly formative quizzes which target key concepts and allow students to assess their own progress. Major components of assessment are integrated within classes, allowing students to actively engage in the process of collecting, managing, summarising, presenting and statistically analysing data. Lecture materials covering basic concepts are available throughout the semester and are supplemented by interactive and applied examples. Small-group sessions provide an opportunity for greater individual attention as developing skills and knowledge are applied to problems grounded in real data.

Assessment strategy and rationale

Research demonstrates that embedding activities linked to assessments into each class helps develop understanding of statistical concepts and their applications. Therefore, a key component of classes each week is students applying statistical concepts covered in class to data they are using as part of their assessment tasks. The first assessment task, the applying statistics report, allows students to use real data that they collect in class and with which they follow a process which mimics a real-world situation of collecting, managing, describing and presenting the data, through statistical analysis, to communication of results. The second assessment task, the practical computer-based test, allows students to demonstrate their ability to manage data, select appropriate statistical tests, conduct the tests and communicate the results. The end-of-semester examination allows students to demonstrate their understanding of statistical concepts, and their ability to interpret and communicate statistical results. 

To pass the unit, students must demonstrate that they have achieved each learning outcome and obtained a total mark of 50% in the unit as the minimum standard.

Overview of assessments

Representative texts and references

Baldi, B., & Moore, D. S. (2018). The practice of statistics in the life sciences (4th ed.). W.H. Freeman, Macmillan Learning. 

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. 

Dytham, C. (2011). Choosing and using statistics : a biologist’s guide (3rd ed.). Wiley-Blackwell.

Field, A. P. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications. 

Kirkwood, B. R., & Sterne, J. A. C. (2003). Essential medical statistics (2nd ed.). Blackwell Pub. 

Moore, D. S. Notz, W., & Fligner, M. A.(2021). The basic practice of statistics (9th ed.). Macmillan Education. 

Portney, L. G. (2020). Foundations of clinical research: Applications to practice (4th ed.). F. A. Davis