The Psychology of Bayesian Reasoning
Abstract
Most psychological research on Bayesian reasoning since the 1970s has used a type of problem that tests a certain kind of statistical reasoning performance. The subject is given statistical facts within a hypothetical scenario. Those facts include a base-rate statistic and one or two diagnostic probabilities. The subject is meant to use that information to arrive at a posterior probability estimate. Bayesian reasoning benefits from the use of visual representations of pertinent statistical information which further clarify nested-set relations to help individuals visualize the nested-set relations and how such information ought to be used to compute the posterior probability. A remarkable feature of the standard approach to studying Bayesian reasoning is its inability to reveal how people revise their beliefs or subjective probabilities in light of newly acquired evidence. Given that standard Bayesian reasoning tasks involve no assessment of a prior probability, they should be seen for what they are: conditional probability judgment tasks that require the combination of statistical information. Future research on Bayesian reasoning would benefit from a richer conceptualization of what it is to be Bayesian and from better discussion of whether being non-Bayesian is necessarily irrational. Future work would also benefit by breaking free of the typical methodological approach. I hope my comments illustrate that there are good opportunities for future work to advance our understanding of how people revise or update their beliefs.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 21, 2014
- Accession Number
- AD1017671
Entities
People
- David R Mandel
Organizations
- Defence Research and Development Canada