BasicBayes: A tutor system for simple Bayesian inference

Abstract

To date, attempts to teach Bayesian inference to nonexperts have not met with much success. BasicBayes, the computerized tutor presented here, is an attempt to change this state of affairs. BasicBayes is based on a novel theoretical framework about Bayesian reasoning recently introduced by Gigerenzer and Hoffrage (1995). This framework focuses on the connection between “cognitive algorithms” and “information formats.” BasicBayes teaches people how to translate Bayesian text problems into frequency formats, which have been shown to entail computationally simpler cognitive algorithms than those entailed by probability formats. The components and mode of functioning of BasicBayes are described in detail. Empirical evidence demonstrates the effectiveness of BasicBayes in teaching people simple Bayesian inference. Because of its flexible system architecture, BasicBayes can also be used as a research tool.