Reasoning from causal and noncausal conditionals: testing an integrated framework

We suggest and test an integrated framework explaining how the interpretation of and the reasoning from causal conditionals (e.g., "If you fertilize a flower it will bloom") depend on exceptions. In the model availability of exceptional situations (e.g., "the flower was not watered enough") reduces the subjective conditional probability of the consequent given the antecedent, P(qlp). The conditional probability corresponds to the subjective degree of belief in the conditional, P(p -> q). The degree of belief in the conditional affects the willingness to accept the valid inferences modus ponens (MP) and modus tollens (MT). Additionally to this probabilistic pathway the framework contains a mental model pathway: a direct influence of exceptional situations on the willingness to accept MP and MT. Three internet-based experiments supported the framework for causal but not for arbitrary conditional statements in which no meaningful relation between antecedent and consequent was present.