PSYC323 - Research Design and Data Analysis 3

Year

Credit points

Campus offering

Prerequisites

PSYC226 Research Design and Data Analysis 2 OR PSYC206 Research Design and Statistics II

Incompatible

PSYC311 Research Design and Statistics III

Teaching organisation

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  data analysis, as well as on the appropriate values and ethical principles underlying research in psychology. The unit continues the students' training in research design and data analysis, which is part of the research toolbox of psychologists, both as researchers themselves, and as practitioners. Like PSYC226, the unit will teach data 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 qualitative analyses (c) conduct and interpret factorial analysis of variance for independent groups, repeated measures and mixed designs, and (d) conduct and interpret multiple regression analysis, including standard and hierarchical forms of model building. In achieving objectives  students will learn to use  software packages (e.g., SPSS, jamovi, JASP, R, Nvivo) 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.

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 qualitative designs
• Qualitative analysis (i.e., thematic analysis, grounded theory, ethnography, narrative analysis)
• Ethical considerations in qualitative research
• Ethical considerations in Indigenous Australian research
• Revision of one-way ANOVA, factorial designs
• Factorial analysis of variance (independent groups, repeated measures, mixed designs)
• 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 software packages (e.g., SPSS, jamovi, JASP, R, Nvivo) to conduct analysis techniques covered in this unit
• Interpretation and reporting of results for statistical techniques covered in this unit

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 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 packages (e.g., SPSS, jamovi, JASP, R, Nvivo), the interpretation of the software’s statistical output, qualitative analysis procedures 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.

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 qualitative analysis report which requires students to conduct, interpret and report on the results of a qualitative analysis. 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

Representative texts and references

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

Cozby, P. C. & Bates, S. (2019). Methods in behavioural research (14th ed). McGraw-Hill.

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

Howitt. (2019). Introduction to qualitative research methods in psychology : Putting theory into practice (Fourth edition.). Pearson.

National Health and Medical Research Council. (2018). Ethical conduct in research with Aboriginal and Torres Strait Islander Peoples and communities: Guidelines for researchers and stakeholders. https://www.nhmrc.gov.au/about-us/resources/ethical-conduct-research-aboriginal-and-torres-strait-islander-peoples-and-communities

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