PSYC206 - Research Design and Statistics II

Year

Credit points

Campus offering

Prerequisites

PSYC104 Research Design and Statistics I

Teaching organisation

Unit rationale, description and aim

Psychology is the discipline devoted to the scientific study of human behaviour. As such, when training to be a psychologist students are, at the most fundamental level, training to be a scientist. 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 PSYC104 Research Design and Statistics 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 is one of three units in the APAC accredited sequence that aims to develop foundational competencies in research methods and statistics.

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 - Distinguish between different research methods and research designs employed in psychological research. Identify the advantages and disadvantages of between subjects and repeated measures designs and describe the various methods of experimental control employed in such designs (GA4, GA5, GA8);

LO2 - Conduct and interpret an ANOVA using a statistical software package (e.g., SPSS, jamovi, JASP, R) for research designs comprising one independent variable (for the case of between subjects and repeated measures designs) (GA4, GA5, GA8, GA10);

LO3 - Conduct an ANOVA and perform appropriate follow-up tests, report and interpret the results in relation to a research question, producing a written research report adhering to APA 6th edition format (GA4, GA5, GA8, GA10);

LO4 - Identify situations when the assumptions of parametric tests have been violated and recognise when specific non-parametric tests are required (e.g., chi-square, non-parametric correlations, non-parametric equivalents of t-tests and ANOVA). Demonstrate proficiency in conducting and interpreting these non-parametric analyses (GA4, GA5, GA8, GA10);

LO5 - Discriminate between planned contrasts and post-hoc tests. Identify simple and appropriate methods for controlling the Type I error rate and explain their calculation (GA4, GA5, GA8, GA10);

LO6 - Conduct simple linear regression analyses using a statistical software package (e.g., SPSS, jamovi, JASP, R), interpret the results and make predictions from these analyses (GA4, GA5, GA8, GA10).

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 

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

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  
• 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  
• Use of a statistical software package (e.g., SPSS, jamovi, JASP, R) to conduct statistical techniques covered in this unit  

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. 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 SPSS, the interpretation of SPSS output, and the write up of results.

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.  

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

Representative texts and references

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

Cozby, P. C. & Bates, P. C. (2015). Methods in behavioural research (12th ed.). McGraw-Hill Education.  

Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). Sage Publications.  

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

Gravetter, F., & Wallnau, L. (2017). Statistics for the behavioral sciences. (10th ed.). Cengage Learning.

Harris, P. (2008). Designing and reporting experiments in psychology. (3rd ed.). Open University Press.  

Howell, D. (2013). Statistical methods for psychology (8th ed.). Wadsworth Cengage Learning.

Navarro, D.J. Learning statistics with R: A tutorial for psychology students and other beginners (Version 0.60). Freely available: https://learningstatisticswithr.com/lsr-0.6.pdf

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

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