Representativeness Heuristic

Kahneman and Tversky's finding that people judge probability based on how well something REPRESENTS its category—how well a specific case matches the prototype of its category—rather than on statistical base rates. 'Steve is shy and organized' → people judge him as more likely to be a librarian than a salesperson, even though salespeople vastly outnumber librarians (base rate). The representativeness heuristic produces: base rate neglect (ignoring prior probabilities), conjunction fallacy (specific scenarios seeming more probable), gambler's fallacy (expecting random sequences to 'look' random), and insensitivity to sample size (treating small samples like large ones).

When to use it

When probability judgments are based on prototype matching rather than frequency; when small samples are being treated as representative; when base rates are being ignored in favor of descriptive similarity; when any of the downstream biases (conjunction fallacy, gambler's fallacy, base rate neglect) are operating.

How it can help

When the representativeness heuristic is triggered (a case seems to 'fit' a category): pause and check the base rate. The diagnostic: 'am I judging probability by how well this matches my mental prototype, or by actual frequency data?' In hiring: a candidate who 'looks like' a successful hire (representativeness) may be less likely to succeed than base rates suggest. In investing: a company that 'looks like' a winner may not be one. The correction: always multiply representativeness-based probability by the base rate of the category.