Representativeness heuristic

Representativeness heuristic is a cognitive shortcut in which people judge the probability of an event by how similar it is to a prototype or stereotype, rather than by base-rate frequency or statistical reasoning. It was identified by Daniel Kahneman and Amos Tversky as one of the core biases in human judgment under uncertainty. When asked whether a shy, precise, mathematically inclined person is more likely to be a librarian or a farmer, most people choose 'librarian' — not because the base rate supports it (there are far more farmers than librarians), but because the description matches the stereotype of a librarian.\n\nThe heuristic is not merely an error; it is a fast and often useful way to navigate a world where full information is unavailable and complete computation is impossible. But it systematically produces errors when base rates are extreme, when sample sizes are small, and when randomness is involved. The representativeness heuristic explains why people see patterns in noise, believe in the 'hot hand' in basketball, and fall for conspiracy theories: the narrative feels representative of the phenomenon, so it must be true.\n\n\n