Credit points


Campus offering

No unit offerings are currently available for this unit



Teaching organisation

3 contact hours per week for twelve weeks or equivalent.

Unit rationale, description and aim

Psychology is the discipline devoted to the scientific study of human behaviour. As such, when training as a psychologist students are, at the most fundamental level, training as a scientist. This unit introduces students to some of the tools of the scientist's toolbox, including basic principles of research methodology. In addition to this, the unit will introduce students to the use of statistics as an instrument for characterising, understanding and extracting information from data and observations. Students will learn about (a) data measurement, collection and organisation, (b) the use and reporting of descriptive statistic information (central tendency and variability), and (c) the use of basic inferential statistic tests to answer research questions. This will involve learning the concept of null hypothesis significance testing and its application to measures of association and difference, in conjunction with issues of power and effect size. Finally, students will be trained in the use of a statistical software package (e.g., SPSS, jamovi, JASP, R) with a focus on creating data files and obtaining descriptive statistics, and estimating correlations and t-tests. As a whole, this unit is one of three units in the Australian Psychology Accreditation Council's accredited sequence designed to develop foundational competencies in research methods and statistics, and to introduce the appropriate values and ethical principles underlying research in psychology.

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 - Recognise psychology as a science and the importance of research in the development of the knowledge base, and identify ethical principles that need to be adhered to during the research enterprise (GA5);

LO2 - Identify the basic concepts of research methodology and design, discriminate between experimental and non-experimental designs, and determine the implications of using one versus the other (GA4, GA5);  

LO3 - Demonstrate basic understanding of the steps underlying research development, including the development of research questions, formulation of hypotheses, operationalisation of variables, and the choice of study design (GA4, GA5); 

LO4 - Identify the scale of measurement of a variable, and the most appropriate methods for presenting and interpreting data for that variable (both in terms of visual representations and use of descriptive statistics) (GA4, GA5); 

LO5 - Select, conduct, and interpret the appropriate statistical test (from among those covered in the unit) to be used for a given research question, and report the results, including measures of effect size and confidence intervals, using APA reporting guidelines (GA4, GA5, GA7, GA9); 

LO6 - Use of a statistical software package (e.g., SPSS, jamovi, JASP, R) to create and modify data files, generate graphs, obtain a range of descriptive statistics, and correlation statistics and t-tests (GA5, GA8). 

Graduate attributes

GA4 - think critically and reflectively 

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

GA7 - work both autonomously and collaboratively 

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

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


Topics will include: 

  • Basic principles of experimental and non-experimental methodology and research design.  
  • Ethical issues in research, including conducting research with diverse populations (with specific reference to relevant sections of the Australian Psychological Society’s Code of Ethics and the Ethical Guidelines of the Australian National Practice Standards for the Mental Health Workforce)  
  • Descriptive statistics including principles and scales of measurement, methods of organising and presenting data  
  • Measures of central tendency and variability, and the normal distribution  
  • Overview of probability and sampling distributions  
  • Introduction to hypothesis testing principles and application of t-tests  
  • Confidence intervals 
  • Statistical power and effect size  
  • Correlation  
  • A statistical software package (e.g., SPSS, jamovi, JASP, R)  will be introduced and will include the following topics : creating and modifying data files; descriptive statistics; graphs; basic inferential statistics including correlation and t-tests    
  • Basic principles of qualitative research methodology 

Learning and teaching strategy and rationale

This unit is primarily delivered face-to-face. Students have 3 contact hours per week which involve a 2 hour lecture and a 1 hour tutorial. Some lectures may be delivered online (or partly online) with the face-to-face time devoted to activities designed to consolidate problem solving skills. The tutorial program is designed to provide training in the use of a statistical software package (e.g., SPSS, jamovi, JASP, R) and to provide students with an opportunity to complete hands-on activities that support learning of basic concepts. In addition to this, and to increase engagement with the unit content on a regular basis, the unit includes use of online quizzes for students to track their progress and identify problem areas with performance, as well as to ensure regular provision of feedback.

Assessment strategy and rationale

In order to successfully complete this unit, students need to complete and submit all of the assessment tasks. In addition to this, students must obtain an aggregate mark of at least 50% to pass the unit.  

There are three components involved in assessment of the unit. First, the online weekly exercises (running from week 3 to week 12) are open book quizzes that present students with multiple choice questions that have been programmed to deliver detailed feedback on performance. They are designed to support students to (a) maintain a regular study habit and (b) identify problem areas in understanding that may be addressed with further support from staff. The data analysis assignment is designed so that students demonstrate their ability to identify a research question and use a statistical software package (e.g., SPSS, jamovi, JASP, R) to conduct the appropriate analysis to answer said research question. In addition to this, students will demonstrate their ability to interpret and report the results and the conclusion of their analysis. The final exam allows student to demonstrate their understanding, consolidation and application of the content covered in the unit.

Overview of assessments

Brief Description of Kind and Purpose of Assessment TasksWeightingLearning OutcomesGraduate Attributes

Weekly online exercises (OE) (no time limit, open book) 

Each exercise will assess student engagement with the content on a weekly basis, and provide the opportunity for students to get early and detailed feedback on their understanding of the concepts covered in class.


LO1, LO2, LO3, LO4, LO5, LO6

GA4, GA5, GA7, GA8, GA9

Data Analysis Assignment (800 words and data analysis work) 

Students will be provided with a research question and a set of data. Students will use the data to conduct the statistical analyses appropriate to answer the research question and write a results section in which students report and interpret the statistical information obtained.


LO3, LO4, LO5, LO6

GA4, GA5, GA7, GA8, GA9

Final Exam (2.0 hours) 

Students will demonstrate their understanding of the statistical and research design topics covered in the unit, with an emphasis on problem solving.


LO1, LO2, LO3, LO4, LO5, LO6

GA4, GA5, GA7, GA8, GA9

Representative texts and references

Allen, P., Bennet, K., & Heritage, B. (2019). SPSS Statistics: A Practical Guide (4th ed.). Cengage.  

American Psychological Association (2019). Publication manual of the American Psychological Association (7th ed.). American Psychological Association.

Aron, A., Aron, E. N., & Coups, E. J. (2019). Statistics for the behavioral sciences. A brief course (6th ed.). Pearson Education.  

Field, A. (2017). Discovering statistics using IBM SPSS. (5th ed.). Sage. 

Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage.

Gravetter, F., & Wallnau, L. (2016). Statistics for the behavioral sciences. (10th ed.). Cengage. 

Graziano, T., & Raulin, M. (2013). Research methods: A process of enquiry (8th ed.). Pearson.  

Howell, D. C. (2016). Fundamental Statistics for the Behavioral Sciences (9th ed.). Cengage.  

Navarro, D.J. Learning statistics with R: A tutorial for psychology students and other beginners (Version 0.60). Freely available:

Navarro, D.J. & Foxcroft, D.R. (2019). Learning statistics with jamovi : A tutorial for psychology students and other beginners. (Version 0.70). DOI: 10.24384/hgc3-7p15

Navarro, D.J., Foxcroft, D.R., & Faulkenberry, T.J. (2019). Learning statistics with JASP: A tutorial for psychology students and other beginners. Freely available:

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