Unit rationale, description and aim
Psychology is the discipline devoted to the scientific study of human behaviour and mental processes. This unit continues student's training in research design and statistical analysis, which is part of the research toolbox of psychologists. This unit will expand students' knowledge and understanding of basic principles of research design and statistical analysis (using a statistical software package: e.g. SPSS, jamovi, JASP, R) that were developed in PSYC110 Research Design and Data Analysis I. In particular, it will focus on the simplest case of research involving one dependent variable (or outcome) and one independent (or predictor) variable. The unit will focus on single factor designs (between subjects and repeated measures) and the associated statistical technique of one-way analysis of variance (ANOVA), as well as correlational designs using simple linear regression. This unit will also include an introduction to qualitative methods including data collection and assessing the credibility, rigour, and trustworthiness of qualitative data analysis. This unit is the second of three units in the APAC accredited sequence that aims to develop foundational competencies in research methods and data analysis.
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.
Distinguish between different research methods and...
Learning Outcome 01
Demonstrate an understanding of the key theoretica...
Learning Outcome 02
Conduct, interpret and report an ANOVA using a sta...
Learning Outcome 03
Identify situations when the assumptions of parame...
Learning Outcome 04
Conduct simple linear regression analyses using a ...
Learning Outcome 05
Content
Topics will include:
- Interpretation and reporting of results for statistical techniques covered in this unit
- Experimental, quasi experimental and non-experimental approaches to research involving a single independent/predictor variable and a continuous dependent variable
- Experimental control and internal validity
- Research design using an Indigenous Research Framework
- Non-parametric equivalents of independent groups and repeated measures t-tests and Pearson’s correlation
- One-way ANOVA (between subjects and repeated measures designs)
- Assumptions of one-way ANOVA
- Non-parametric equivalents of one-way ANOVA (i.e., Kruskal-Wallis and Friedman’s ANOVA)
- Chi-square
- Simple linear regression
- Qualitative methods (design, data collection, and credibility)
- Use of a statistical software package (e.g., SPSS, jamovi, JASP, R) to conduct 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 development of the associated graduate attributes. There are three assessment components. First, a mid-semester examination allows students to demonstrate their understanding, consolidation and application of the content covered in the unit and enables students to receive timely feedback on their progress in the unit. Second, data analysis reports provide students with two research questions, each with an associated set of data. Students are required to (a) identify the statistical analyses that are appropriate to answer each research question, (b) conduct appropriate analyses using a statistical software package (e.g., SPSS, jamovi, JASP, R), and (c) report and interpret the results in a write-up that adheres to the format of a results and discussion section of a research report. Finally, the end-of-semester examination allows students to demonstrate their understanding, consolidation, and application of the content covered in the unit.
Overview of assessments
Assessment Task 1 - Mid-semester Examination ...
Assessment Task 1 - Mid-semester Examination
The examination will comprise multiple choice and short answer questions and will assess knowledge and understanding of unit content.
The purpose of this assessment is to provide students with timely and formative feedback on their progress in the unit.
20%
Assessment Task 2 - Data Analysis Reports &n...
Assessment Task 2 - Data Analysis Reports
Students will be provided with two research questions and their corresponding data sets and will be required to identify, conduct, interpret and report the results of the appropriate statistical analyses. The purpose of this assessment is to develop skills in the use of a statistical software package (e.g., SPSS, jamovi, JASP, R) for statistical analysis, and to provide the opportunity to develop skills in reporting and discussing the results of statistical analyses in a research report format.
40%
Assessment Task 3 - End-of-semester Examination&n...
Assessment Task 3 - End-of-semester Examination
The examination will comprise multiple choice and short answer questions and will assess knowledge and understanding of unit content.
The purpose of this assessment is to assess students’ mastery of the content covered in the unit.
40%
Learning and teaching strategy and rationale
This unit has the equivalent of three contact hours per week over twelve weeks which involves lectures and tutorials. The lectures will introduce students to the content of the unit and are designed to facilitate understanding of the key concepts of the analyses under study. The tutorial program is designed to provide practical skills in the conduct and interpretation of the analyses taught in lectures. In particular, the tutorials focus on providing training in the use of a statistical package, the interpretation of output from a statistical package, and the write up of results.