Credit points


Campus offering

No unit offerings are currently available for this unit



Teaching organisation

150 hours of focused learning

Unit rationale, description and aim

The application and interpretation of statistical techniques is critical to the practice of science. Since measurement is foundations to science, it is important that practitioners are able to competently handle the tools that allow comparisons of such measurements and are able to draw valid conclusions from them.

This unit considers the most commonly encountered types of experimental design and variable types and provides students with the skills needed to describe data, transform it where required, apply appropriate statistical tests and interpret the results of such tests. Students are provided with the foundational knowledge to do this well as the skills and techniques to implement such tests using statistical software.

This unit provides students with the opportunity to acquire understanding and skills needed to apply appropriate statistical tools for a given situation, experimental design and variable type.

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.

On successful completion of this unit, students should be able to:

LO1 - Demonstrate an understanding of and ability to differentiate among variable types and scales of measurement. (GA4,5)

LO2 - Select and produce appropriate graphical representations and descriptive statistics to characterise a data set in terms of distribution, skew, spread and central tendency. (GA4,5,8,9,10)

LO3 - Describe and apply appropriate predictive linear models for the statistical analysis of data using statistical software with justification based on research design, question and variable types. (GA4,5,8,9)

LO4 - Describe potential sources of bias in a given data set and describe techniques to minimise or control for bias including the selection of appropriate alternative statistical analyses. (GA4,5,8,9)

Graduate attributes

GA4 - think critically and reflectively 

GA5 - demonstrate values, knowledge, skills and attitudes appropriate to the discipline and/or profession 

GA8 - locate, organise, analyse, synthesise and evaluate information 

GA9 - demonstrate effective communication in oral and written English language and visual media 

GA10 - utilise information and communication and other relevant technologies effectively.


Topics will include: 

  • Introduction and overview of biostatistics 
  • Variability and measurement error 
  • Using statistical software 
  • Summarising data using descriptive statistics 
  • Exploring data with graphs 
  • Identifying and controlling for bias 
  • Hypothesis testing 
  • Non-parametric models 
  • Correlation and linear regression 
  • Comparing two means 
  • Comparing several means using analysis of variance  

Learning and teaching strategy and rationale

This unit of study predominantly engages students in active approaches to their learning. Weekly lectures will generally be followed by an interactive simulation that requires students to apply the concepts of that topic. 

A weekly tutorial session provides an opportunity for greater individual attention for students as they apply the skills and knowledge in a particular topic to problems that are grounded in real data collected by them. These classes also allow for discussion of issues that arise from application of statistical techniques in various contexts.

Students use statistical software in weekly practical classes held in a computer laboratory. These classes use the data collected by students and develop the skills and confidence with these important statistical tools. Online support, supplementary materials and channels of communication are provided to students via LEO.

Assessment strategy and rationale

In this unit key statistical concepts are carefully unpacked and applied to real situations. The assessment strategy supports this approach with a series of weekly quizzes that target those concepts. 

The computer-based assignments relate directly to the real data that students have been using during the semester in their practical sessions. The assignments require them to use statistical software to describe, analyse, test and draw conclusions from those data. The assignments are well supported by carefully paced classes targeting key theory and concepts.  

The end-semester examination allows students to demonstrate the basic skills and knowledge that are required for this unit. 

Overview of assessments

Brief Description of Kind and Purpose of Assessment TasksWeightingLearning OutcomesGraduate Attributes

Computer (LEO) Quizzes on material from lectures, tutorials and practical classes.


LO1, LO2

GA4, GA5 

Computer-based Analyses: Assessment of understanding of material covered in Practical classes to be submitted via Turnitin.


LO1, LO2, LO3

GA4, GA5, GA8, GA9, GA10 

Final (LEO) Examination: Requires students to demonstrate an understanding of all aspects of the unit.


LO1, LO2, LO4 

GA4, GA5, GA8, GA9 

Representative texts and references

Dytham C. (2011) Choosing and Using Statistics: A Biologist’s Guide. 3rd Edn. Wiley-Blackwell, Oxford. 

Baldi B. and Moore D.S. (2014) The Practice of Statistics in the Life Sciences. 3rd Edition. W.H. Freeman and Co., New York. 

Field A. (2013) Discovering statistics using IBM SPSS statistics. 4th Edn. Sage, London. 

Fowler J., Cohen L. and Jarvis P. (1998) Practical Statistics for Field Biology 2nd Edn. Wiley, Chichester  

Fowler J., Jarvis P. and Chevannes M. (2002) Practical Statistics for Nursing and Health Care. Wiley, Chichester  

Moore D. S., Notz W. I., Fligner M. A. (2015) The basic practice of statistics.7th Edn. W.H. Freeman & Co., New York. 

Portney L. G. & Watkins, M. P. (2008) Foundations of clinical research: applications to practice. Prentice Hall, Upper Saddle River. 

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