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 is one of three units in the APAC accredited sequence designed to develop foundational competencies in research methods and statistics, as well as on the appropriate values and ethical principles underlying research in psychology. The unit continues the students' training in research design and statistical analysis, which is part of the research toolbox of psychologists, both as researchers themselves, and as practitioners. Like PSYC206, the unit will teach statistical analysis techniques in the context of the research design in which they are used. The unit will extend the students' knowledge and practical skills to the analysis of experimental and non-experimental data in complex research questions, where more than one independent/predictor variable is included. Students will learn how to (a) critically evaluate the internal validity of research studies, (b) conduct and interpret factorial analysis of variance for independent groups, repeated measures and mixed designs, and (c) conduct and interpret multiple regression analysis, including standard and hierarchical forms of model building. In achieving objectives (b) and (c), students will learn to use a statistical software package (e.g., SPSS, jamovi, JASP, R) to conduct all analyses.
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.
Differentiate experimental and non-experimental de...
Learning Outcome 01
Identify potential threats to internal validity an...
Learning Outcome 02
Evaluate complex factorial models with more than o...
Learning Outcome 03
Conduct and interpret factorial analyses of varian...
Learning Outcome 04
Recognise research questions that require the use ...
Learning Outcome 05
Conduct and interpret multiple linear regression a...
Learning Outcome 06
Content
Topics will include:
- Distinction between experimental, quasi-experimental and non-experimental designs for the case with more than one independent/predictor variable
- Judging the quality of research studies: internal and external validity
- Revision of one-way ANOVA, Factorial designs
- Factorial Analysis of Variance (IG, RM, mixed)
- Revision of correlation and simple linear regression
- Standard multiple regression and hierarchical multiple linear regression
- The assumptions of linear regression and assessment of outliers/influential cases
- Categorical variables in regression
- Use of a statistical software package (e.g., SPSS, jamovi, JASP, R) to conduct statistical techniques covered in this unit
- Interpretation and reporting of results for statistical techniques covered in this unit
Assessment strategy and rationale
In order to successfully complete this unit, students must:
- complete and submit all of the assessment tasks listed in the table below
- obtain an aggregate mark of at least 50%
- demonstrate achievement of each learning outcome
The assessment tasks have been designed to allow students to demonstrate the achievement of the learning outcomes of the unit and develop the associated graduate attributes. There are three components involved in assessment of the unit. First, a research critique assignment requires students to read, reflect on and write a critique of a research study. Second, a data analysis report will include an opportunity to: (a) identify the statistical analysis that is appropriate to answer specific research questions, (b) conduct said analyses using the statistical software package, and (c) report and interpret the results. The final exam allows students to demonstrate their understanding, consolidation and application of the content covered in the unit.
Overview of assessments
Assessment Task 1 - Research Critique Students wi...
Assessment Task 1 - Research Critique
Students will evaluate a research study, thus demonstrating their understanding of research methodology.
25%
Assessment Task 2 - Data Analysis Report Students...
Assessment Task 2 - Data Analysis Report
Students will be required to identify, conduct, interpret and report the results of a statistical analysis that is appropriate for a specified research question. This task enables students to demonstrate the ability to apply the knowledge acquired in this unit.
35%
Assessment Task 3 - End of Semester Exam Students...
Assessment Task 3 - End of Semester Exam
Students will be required to demonstrate an understanding of the main constructs discussed throughout this unit.
40%
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 lectures will introduce students to the content of the unit and are designed to facilitate understanding of the main concepts of the analyses under study. The tutorial program is designed to provide practical skills in the conduct and interpretation of the analysis taught in the lecture. In particular, the tutorials provide training in the use of statistical software package (e.g., SPSS, jamovi, JASP, R), the interpretation of the software’s statistical output, and the write up of results. In addition to the data analysis exercises completed during tutorial time, students are provided with practice weekly exercises to complete in their own time and for which the answers are provided a few days later to assist in self-assessment of performance.