Estimation & Judgment
Psychological Biases
🎯 Estimation & Judgment
19 biases in this category
Biases that affect how we estimate probabilities, quantities, and make judgments about uncertain events.
Anchoring Bias
The cognitive bias where people rely too heavily on the first piece of information they encounter (the "anchor") when making decisions, with subsequent judgments being insufficiently adjusted away from that anchor even when it is arbitrary or irrelevant.
Availability Heuristic
The mental shortcut of estimating the likelihood of events based on how easily examples come to mind, leading to overestimation of dramatic, recent, or emotionally charged events and underestimation of common but less memorable ones.
Dunning-Kruger Effect
A cognitive bias where people with limited knowledge or competence in a domain significantly overestimate their own abilities, while genuine experts tend to underestimate theirs—incompetence prevents recognition of incompetence.
Curse of Knowledge
The difficulty that well-informed people have in thinking about problems from the perspective of lesser-informed people, making it hard to teach, communicate, or empathize with those who lack their knowledge.
False Consensus Effect
The tendency to overestimate the extent to which others share our beliefs, opinions, and preferences, assuming our views are more common and normative than they actually are.
Illusion of Transparency
The tendency to overestimate the degree to which our internal states (emotions, thoughts, intentions) are apparent to others, assuming we are more "readable" than we actually are.
Optimism Bias
The systematic tendency to be overly optimistic about the outcomes of planned actions, overestimating the likelihood of positive events and underestimating the likelihood of negative events happening to oneself.
Pessimism Bias
The opposite of optimism bias—a tendency to overestimate the probability of negative outcomes, often associated with depression and anxiety, leading to excessive caution and missed opportunities.
Spotlight Effect
The tendency to believe that other people are paying more attention to our appearance and behavior than they actually are, as if a spotlight were shining on us highlighting our every flaw.
Planning Fallacy
The systematic tendency to underestimate the time, costs, and risks of future actions while overestimating the benefits, even when we have experience with similar tasks taking longer than expected.
Impact Bias
The tendency to overestimate the intensity and duration of future emotional reactions to events, both positive and negative—we think winning the lottery will make us happier longer than it does, and that setbacks will devastate us more than they do.
Gambler's Fallacy
The mistaken belief that if something happens more frequently than normal during a given period, it will happen less frequently in the future (or vice versa), when in reality each event is independent.
Hot-Hand Fallacy
The belief that a person who has experienced success has a greater chance of continued success, even in random or independent events—the flip side of the gambler's fallacy.
Base Rate Neglect
The tendency to ignore general statistical information (base rates) in favor of specific information about individual cases, leading to poor probability judgments.
Hard-Easy Effect
A cognitive bias in which people overestimate their ability to accomplish difficult tasks while underestimating their ability on easy tasks, showing poor calibration between confidence and actual performance.
Restraint Bias
The tendency to overestimate one's ability to control impulsive behavior, leading people to expose themselves to temptation because they believe (often wrongly) they can resist it.
Worse-Than-Average Effect
The tendency to believe oneself to be below average at difficult or specialized tasks, the inverse of illusory superiority—common when people compare themselves to perceived experts.
Conjunction Fallacy
The error of assuming that specific conditions are more probable than more general ones, violating basic probability rules.
Insensitivity to Sample Size
The failure to appreciate that the variability of sample statistics decreases as sample size increases, leading people to draw strong conclusions from small samples that could easily be due to chance.