Naive probability: A mental model theory of extensional reasoning

This article outlines a theory of naive probability. According to the theor y, individuals who are unfamiliar with the probability calculus can infer t he probabilities of events in an extensional way: They construct mental mod els of what is true in the various possibilities. Each model represents an equiprobable alternative unless individuals have beliefs to the contrary, i n which case some models will have higher probabilities than others. The pr obability of an event depends on the proportion of models in which it occur s. The theory predicts several phenomena of reasoning about absolute probab ilities, including typical biases. It correctly predicts certain cognitive illusions in inferences about relative probabilities. It accommodates reaso ning based on numerical premises, and it explains how naive reasoners can i nfer posterior probabilities without relying on Bayes's theorem. Finally, i t dispels some common misconceptions of probabilistic reasoning.