Conditional reasoning in context: a dual-source model of probabilistic inference.

A dual-source model of probabilistic conditional inference is proposed. According to the model, inferences are based on 2 sources of evidence: logical form and prior knowledge. Logical form is a decontextualized source of evidence, whereas prior knowledge is activated by the contents of the conditional rule. In Experiments 1 to 3, manipulations of perceived sufficiency and necessity mapped on the parameters quantifying prior knowledge. Emphasizing rule validity increased the weight given to form-based evidence relative to knowledge-based evidence (Experiment 1). Manipulating rule form (only-if vs. if-then) had a focused effect on the parameters quantifying form-based evidence (Experiment 3). The model also provides a parsimonious description of data from the so-called negations paradigm and adequately accounts for polarity bias in that paradigm (Experiment 4). Relationships to alternative conceptualizations of conditional inference are discussed.