A RATIONAL ANALYSIS OF THE SELECTION TASK AS OPTIMAL DATA SELECTION

Human reasoning in hypothesis-testing tasks like Wason's (1966, 1968) selection task has been de picted as prone to systematic biases. However, performance on this task has been assessed against a now outmoded falsificationist philosophy of science. Therefore, the experimental data is reassessed in the light of a Bayesian model of optimal data selection in inductive hypothesis testing. The model provides a rational analysis(Anderson, 1990) of the selection task that fits well with people's performance on both abstract and thematic versions of the task. The model suggests that reasoning in these tasks may be rational rather than subject to systematic bias.