Proceedings of the Annual Meeting of the Cognitive Science Society

Illusions of causality arise when people observe statistically unrelated events and yet form a belief that the events are causally linked. When participants observe a sequence of discrete binary events (e.g., a patient was either administered a treatment or no treatment, and subsequently recovers or does not recover from their illness), the frequency of the putative cause and outcome occurring inflates the illusion of causality. Recently, similar effects have been observed using outcomes of continuous magnitude. Participants are more likely to endorse the causal status of a (completely ineffective) cue if the target outcome (e.g., high magnitude outcomes) occur frequently. Here, we extended these findings by investigating how predictions and causal judgments for a cue of continuous magnitude were affected by the distribution of cue values presented. Participants observed cue values (dose of a fictitious medicine) sourced from either a continuous distribution or from two discrete values, and were followed by outcomes that were either continuous (Experiment 1) or binary in nature (Experiment 2). Our results show that participants were more likely to assume a linear relationship between drug dose and magnitude of recovery when cue dosage were predominantly high than when they were predominantly low.