Research design and statistics 2A: analysis of variance
This module provides foundational training in the principles and skills required for understanding, applying, and conducting psychological research. The module will cover (1) the principles of research and (2) data analysis.
Students will be introduced to the range of statistical techniques, known as Analysis of Variance, extending their inferential tests of group differences for measurement data to situations involving more than two groups. They will learn how to interpret the information that these techniques produce, to better understand and interpret psychological research conducted by others, and conduct psychological research and draw appropriate conclusions from this research.
Main topics include:
- Critical evaluation of research design and analysis, being able to comment appropriately on the design, analysis and interpretation of published research. This includes the evaluation of quantitative research involving the application of Analysis of Variance (ANOVA) to multiple manipulations, or multiple predictors of behaviour.
- Application of the most appropriate form of ANOVA to analyse, report and draw conclusions from quantitative data. This includes the analysis of data sets with multiple predictors or groups, including experiments using a factorial design.
- Understanding of how to measure behaviour, how quantitative data can be collected and analysed in terms of differences between group means, and to appreciate the strengths and limitations of this approach to various research methodologies.
If you complete the course successfully, you should be able to:
- Make appropriate use of a statistical package (e.g. SPSS or R) to perform an analysis of variance (ANOVA).
- Design, analyse and interpret experiments involving multi-group, and factorial designs, including controlling errors among multiple-comparisons; and interpretation of interaction effects.
- Discuss the concepts underlying quantitative research based on estimation of effects and comparison of means, and be able to defend the use of one or both outline the advantages and disadvantages of ANOVA methods.
