Probabilistic theories of reasoning assume that people use their prior knowledge to estimate the conditional probability of q given p and that this probability predicts the acceptance of modus ponens inferences. But how do people reason with unfamiliar conditionals for which they do not have prior knowledge? Reasoning without prior knowledge has been extensively investigated in experiments in which participants were instructed to reason deductively. But it is still not clear how people reason with unfamiliar conditionals when they are instructed (...) to reason as in daily life. Can probabilities also predict reasoning with unfamiliar content? In two experiments we instructed participants to reason as in everyday life and to evaluate conclusions from familiar and unfamiliar conditionals. Results showed that reasoning with familiar conditionals can be predicted by the conditional probability. For unfamiliar conditionals, however, this was not the case. Conclusions from unfamiliar conditionals were accepted more strongly than what could be expected according to their conditional probability. Our findings challenge probabilistic theories of reasoning and suggest that other approaches, such as a dual-strategy model, describe our results more adequately. (shrink)

In previous published research (“Conditionals and Inferential Connections: A Hypothetical Inferential Theory,” Cognitive Psychology, 2018), we investigated experimentally what role the presence and strength of an inferential connection between a conditional’s antecedent and consequent plays in how people process that conditional. Our analysis showed the strength of that connection to be strongly predictive of whether participants evaluated the conditional as true, false, or neither true nor false. In this article, we re-analyse the data from our previous research, now focussing on (...) the semantics of conditionals rather than on how they are processed. Specifically, we use those data to compare the main extant semantics with each other and with inferentialism, a semantics according to which the truth of a conditional requires the presence of an inferential connection between the conditional’s component parts. (shrink)