PB413 Half Unit
Experimental Design and Methods for Behavioural Science
This information is for the 2020/21 session.
Dr Matteo M Galizzi and Dr Dario Krpan
This course is compulsory on the MSc in Behavioural Science. This course is not available as an outside option.
Behavioural science is the scientific study of human behaviour, and it combines research techniques from psychology and economics. The course offers an integrated training in advanced behavioural science methods by introducing students to state-of-the-art techniques that stretch across the spectrum of both disciplines.
The course covers the following topics: randomised controlled experiments in behavioural science, causality, selection bias; online, lab, and field experiments in behavioural science; principles of experimental design; transparency and reproducibility of behavioural science research, pre-registration, pre-analysis plan; best practices in modern behavioural science experiments; tests of hypotheses and sample size calculations for experiments in theory and practice; determining evidential value of behavioural science research, p-curve analysis; measuring preferences, attitudes, beliefs, willingness-to-pay; behavioural game theory and experimental games of strategic interaction; designing behavioural priming experiments and measures that tap into implicit cognition; state-of-the-art physiological research techniques; regression analysis of experimental data in theory and practice; understanding the mechanisms behind behavioural effects by employing experimental-causal-chain, measurement-of-mediation, and moderation-of-process designs.
10 hours of lectures and 10 hours of seminars in the MT.
Additionally, there will be lab help sessions in collaboration with PB4A7
Students will be expected to produce 1 presentation in the LT.
For the formative assignment, students will work in small groups (3-4 students) to produce a presentation in which they will need to propose a design and implementation of a behavioural science experiment entailing the use of (at least) two different software packages introduced in the course.
- Angrist, J.D., Pischke J-S. (2015). Mastering ‘Metrics: the Path from Cause to Effect. Princeton: Princeton University Press.
- Camerer, C.F. (2003). Behavioral Game Theory: Experiments in Strategic Interaction. Princeton: Princeton University Press.
- Dijksterhuis, A., Chartrand, T. L., & Aarts, H. (2007). Effects of Priming and Perception on Social Behavior and Goal Pursuit. In J. A. Bargh, J. A. Bargh (Eds.), Social psychology and the unconscious: The automaticity of higher mental processes (pp. 51-131). New York, NY, US: Psychology Press.)
- Förster, J., & Liberman, N. (2007). Knowledge activation. Social psychology: Handbook of basic principles, 2, 201-231.
- Gawronski, B., & De Houwer, J. (2014). Implicit measures in social and personality psychology. Handbook of research methods in social and personality psychology, 2, 283-310.
- Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.
- Darlington, R. B., & Hayes, A. F. (2016). Regression analysis and linear models: Concepts, applications, and implementation. Guilford Publications.
- Harrison, G.W., List, J.A. (2004). Field experiments. Journal of Economic Literature, XLII, 1009-1055.
- Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014). P-curve: a key to the file-drawer. Journal of Experimental Psychology: General, 143(2), 534-547.
- Spencer, S. J., Zanna, M. P., & Fong, G. T. (2005). Establishing a causal chain: why experiments are often more effective than mediational analyses in examining psychological processes. Journal of Personality and Social Psychology, 89, 845-851.
Report (100%) in the ST.
Students will be expected to write a 3,000 word report. The reports will need to be submitted individually and will require students to elaborate on the group-work undertaken as part of the formative assignment.
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Department: Psychological and Behavioural Science
Total students 2019/20: 41
Average class size 2019/20: 18
Controlled access 2019/20: Yes
Value: Half Unit
Personal development skills
- Team working
- Problem solving
- Application of information skills
- Application of numeracy skills
- Specialist skills