Experiments for Decision Making in Business and Policy

Semester Spring
Level 11
Credit Value 20
Module Co-ordinator Dr David Comerford
Contact Hours 10 x 2 hour Lectures on experimental techniques and 9 x 2 hour group workshops in which students present the readings to the class
Assessment This module is assessed by 60% coursework (made up of 20% for a Quiz, and 40% for a project) and 40% examination.


Increasingly, policymakers and business and strategists are looking for evidence-based arguments to justify decisions.  There are three issues that make this module beneficial to the course:

  • In the digital age, it is very feasible for firms and social entrepreneurs to pilot test their business strategies.
  • Data is rapidly accumulating from experiments that show more effective ways to achieve business and policy goals than would be predicted by the standard economic models.  At the same time, there are more myriad psychological theories, some contradictory, making it hard for practitioners to predict behaviour based on theory.  This module aims to systematise findings from the judgement and decision making literature; to identify anomalous findings that require further research, and to equip students with the skills to undertake that research.
  • Evidence-based decision-making will outperform misapplied theories and trial and error in the long run and so an effective manager or policy maker needs to be aware of biases and to have the skills to test their theory.

Learning Outcomes

This module will provide the students with knowledge and understanding of:

  • The logic of experimentation.
  • Some core theories of judgement and decision making.
  • Types of experiments - what approach is most appropriate to use for which questions.
  • The limits of experimentation - what questions are not amenable to experimentation?  What threats are there to internal validity?  How do we judge external validity?
  • Statistical inference - how might we recognise poor statistical practice in published work?  How do we avoid poor statistical practice in our own research?
  • How to design and conduct an experiment.

This module information is representative of what is included in the module in a given year. Details of actual reading, lectures and coursework may vary year to year and will be available at the beginning of the semester.



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