Naive probability: A mental model theory of extensional reasoning.
Abstract
This article outlines a theory of naive probability. According to the theory, individuals who are unfamiliar with the probability calculus can infer the probabilities of events in an extensional way: They construct mental models of what is true in the various possibilities. Each model represents an equiprobable alternative unless individuals have beliefs to the contrary, in which case some models will have higher probabilities than others. The probability of an event depends on the proportion of models in which it occurs. The theory predicts several phenomena of reasoning about absolute probabilities, including typical biases. It correctly predicts certain cognitive illusions in inferences about relative probabilities. It accommodates reasoning based on numerical premises, and it explains how naive reasoners can infer posterior probabilities without relying on Bayes's theorem. Finally, it dispels some common misconceptions of probabilistic reasoning.
Cites (4)
- Availability: A heuristic for judging frequency and probabilityTversky, Amos, Kahneman, Daniel · 1973 · Cognitive Psychology
- On the psychology of prediction.Kahneman, Daniel, Tversky, Amos · 1973 · Psychological Review
- Design of ExperimentsFisher, R. A. · 1936 · BMJ
- Support theory: a nonextensional representation of subjective probabilityTversky, Amos, Koehler, Derek J. · 1994 · Psychological Review
Cited by (4)
- The Probability Heuristics Model of Syllogistic ReasoningChater, Nick, Oaksford, Mike · 1999 · Cognitive Psychology
- The probability of causal conditionalsOver, David E., Hadjichristidis, Constantinos, Evans, Jonathan St. B.T., Handley, Simon J., Sloman, Steven A. · 2007 · Cognitive Psychology
- Decision Making with Uncertain Reinforcement in Children with Attention Deficit/Hyperactivity Disorder (ADHD)Drechsler, Renate, Rizzo, Patrizia, Steinhausen, Hans-Christoph · 2010 · Child Neuropsychology
- Logical Concepts of (Im)possibility Guide Young Children's Decision‐MakingCesana‐Arlotti, Nicolò, Jáuregui, Sofia, Mazalik, Peter, Nichols, Shaun, Halberda, Justin · 2025 · Developmental Science
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Naive probability: A mental model theory of extensional reasoning. https://app.cochat.ai/papers/10.1037//0033-295x.106.1.62
- The paper
- Johnson-Laird, P. N., Legrenzi, P., Girotto, V., Legrenzi, M. S., & Caverni, J.-P. (1999). Naive probability: A mental model theory of extensional reasoning. Psychological Review. https://doi.org/10.1037//0033-295x.106.1.62
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