MENTAL MODELS AND PROBABILISTIC THINKING

This paper outlines the theory of reasoning based on mental models, an d then shows how this theory might be extended to deal with probabilis tic thinking. The same explanatory framework accommodates deduction an d induction: there are both deductive and inductive inferences that yi eld probabilistic conclusions. The framework yields a theoretical conc eption of strength of inference, that is, a theory of what the strengt h of an inference is objectively: it equals the proportion of possible states of affairs consistent with the premises in which the conclusio n is true, that is, the probability that the conclusion is true given that the premises are true. Since there are infinitely many possible s tates of affairs consistent with any set of premises, the paper then c haracterizes how individuals estimate the strength of an argument. The y construct mental models, which each correspond to an infinite set of possibilities (or, in some cases, a finite set of infinite sets of po ssibilities). The construction of models is guided by knowledge and be liefs, including lay conceptions of such matters as the ''law of large numbers''. The paper illustrates how this theory can account for phen omena of probabilistic reasoning.