Probabilistic reasoning in prediction and diagnosis: Effects of problem type, response mode, and individual differences

Abstract

Abstract In prediction, subset relations require that the probability of conjoined events is never higher than that of constituent events. However, people's judgments regularly violate this principle, producing conjunction errors. In diagnosis, the probability of a hypothesis normatively is often higher for conjoined cues. An online survey used a within‐subjects design to explore the degree to which participants (n = 347) differentiated diagnosis and prediction using matched scenarios and both choice and estimation responses. Conjunctions were judged more probable than a constituent in diagnosis (76%) more often than prediction (64%) and in choice (84%) more often than direct estimation (57%), with no interaction of type of task and response mode. Correlation, regression, and path analyses were used to determine the relationships among individual difference variables and the diagnosis and prediction tasks. Among the correlation findings was that time spent on the task predicted higher conjunction probabilities in diagnosis but not prediction and that class inclusion errors predicted increased conjunction errors in choice but not estimation. Need for cognition and numeracy were only minimally related to reasoning about conjunctions. Results are consistent with the idea that people may misapply diagnostic reasoning to the prediction task and consequently commit the conjunction error. Copyright © 2010 John Wiley & Sons, Ltd.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 10 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.