Proceedings of the Annual Meeting of the Cognitive Science Society

Elicitation methods, such as asking people to produce the deciles of a distribution, are standard practices in policy or applied statistics. However, these approaches often only capture a rough outline of what people know. We investigated whether tasks in which participants generate random sequences of items can be used to elicit people’s implicit beliefs about the distribution of these items. Because it remains unclear if, and at what level of detail, people represent distributions, we applied both decile elicitation and random generation tasks to uncover the kinds of environmental statistics investigated by Griffiths and Tenenbaum (2006). We found that random generation is competitive with decile elicitation in predicting participants’ expectations. Both random generation and decile elicitation revealed that people know the rough shapes of environmental distributions. Random generation, however, goes beyond decile elicitation in establishing the novel finding that people are aware of fine details of environmental distributions