Proceedings of the Annual Meeting of the Cognitive Science Society

We outline a simple way of representing sets of non-normativejudgements that makes them look as similar as possible to nor-mative ones. This representation allows us to view certaintypes of non-normative judgments, such as conjunction falla-cies, as arising from a misestimation of the correlation betweenevents, that might arise when decision-makers have no priorinformation about the frequency of co-occurrence. We sug-gest that decision-makers use the perceived similarity betweenevents to make inferences about correlation, and we describethe results of an experiment showing that judged correlationand violations of independence in probabilistic judgments arestrongly influenced by the perceived similarity between events.