Dr Matteo 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; behavioural science experiments spanning the continuum spectrum from the lab to the field; principles of experimental design; best practices in modern behavioural science experiments; 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; tests of hypotheses and sample size calculations for experiments in theory and practice; p-curve analysis; 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.

The course is delivered in Michaelmas Term over 10 lectures of 1 hour (1 per week, over weeks 1-5, and 7-11) and 10 weekly seminar sessions of 1 hour (1 per week, over weeks 1-5, and 7-11).

Students on this course will have a reading week in Week 6, in line with departmental policy.

Lectures and Seminars:

Week 1

• Lecture 1: Introduction to the Course. The Beauty of Behavioural Science Experiments: Why Randomization Solves the Selection Bias.
• Seminar 1: Building a Simple Behavioural Science Experiment Using Qualtrics.

Week 2

• Lecture 2: Behavioural Science Experiments: from the Lab to the Field. Best Practices in Modern Behavioural Science Experiments.
• Seminar 2: Best Experimental Practices in Practice.

Week 3

• Lecture 3: Principles of Experimental Design.
• Seminar 3: Building a Simple Game of Strategic Interaction: Introduction. 

Week 4

• Lecture 4: Strategic Decision-Making: Introduction to Behavioural Game Theory.
• Seminar 4: Building a Simple Game of Strategic Interaction.

Week 5

• Lecture 5: Behavioural Priming Techniques.
• Seminar 5: Designing Behavioural Priming Experiments.

Week 6

• No lecture: Reading week

Week 7

• Lecture 6: System 1 in Action: Capturing Implicit Cognition.
• Seminar 6: Building a Simple Task to Measure Implicit Cognition.

Week 8

• Lecture 7: Beyond Economics and Psychology: State-of-the-art Physiological Research Techniques.  
• Seminar 7: Physiological Research Techniques in Practice.

Week 9

• Lecture 8: Tests of Hypotheses and Sample Size Calculations for Experiments. Useful Rules of Thumb. P-hacking.
• Seminar 8: Statistical Tests and Sample Size Calculations for Experiments in Practice. P-curve analysis in practice.

Week 10

• Lecture 9: Understanding the Mechanisms Behind Behaviour Change: Experimental-Causal-Chain, Measurement-of-Mediation, and Moderation-of-Process Designs.
• Seminar 9: Analysis of Experimental Data in a Regression Framework in Practice. Experimental-Causal-Chain, Mediation Analysis, and Moderation-of-Process in Practice.

Week 11

• Lecture 10: Measuring Preferences, Attitudes, Beliefs, Willingness-to-pay: State-of-the-art Measures.
• Seminar 10: Experimental-Causal-Chain, Mediation Analysis, and Moderation-of-Process in Practice.

Students will be expected to produce 1 presentation in the LT.

For the formative assignment, you will work in small groups (3-4 students) to produce a 15-minute presentation in which you will need to propose a design and implementation of a behavioural science experiment. Alternatively, you can focus on a piece of research that has already been conducted and produced the data you are planning to use in the future, and you can analyse the design and implementation of this research. More precise instructions about the assignment will be given to you at the start of 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.

You will be expected to write a 3,000 word report. The reports will need to be submitted individually and will require you to elaborate individually on the group-work undertaken as part of the formative assignment. More precise instructions about the assignment will be given to you at the start of the course.

Department: Psychological and Behavioural Science

Total students 2018/19: 11

Average class size 2018/19: 10

Controlled access 2018/19: No

Value: Half Unit