Link to Wikipedia entry
The representativeness heuristic is one of the most widely researched and demonstrated cognitive heuristics (short cuts or rules of thumb putatively built in to the human cognitive system). It was proposed by the psychologists Daniel Kahneman and Amos TverskyDaniel Kahneman and Amos Tversky are pioneering Israeli psychologists whose collaboration profoundly impacted the the science of judgment and decision making and behavioral economics. Their... in the 1970s as one of the “big three” in cognitive heuristics (along with AvailabilityThe Availability Heuristic is an automatic cognitive process by which individuals estimate the likelihood or frequency of an event based on how easily examples or... and Anchoring) that, while often effective or adaptive, leads to systematic errors or biases. This particular heuristic treats individual cases (such as people or cars) or events (such as flips of a coin), or samples of those cases or events, such as a series of flips of a coin, as being more representative of the population or event distribution from which the cases were drawn than probability theory would predict given available information.
This heuristic has been associated with a wide range of systematic errors or biases in decision making, including base-rate neglect (the tendency to ignore known population frequencies when assessing the likelihood that an event belongs to a particular category); the “law of small numbers,” (ironically termed in contrast to the normatively well-founded law of large numbers), whereby people expect small samples of events or cases to look more like the populations from which they were drawn than is appropriate or, alternatively, overestimate the diagnostic value of small samples for generalizing about the population from which they were drawn; and “the conjunction fallacyIn decision science, bias refers to systematic and predictable deviations from accepted models of rationality. In scientific language, "systematic" and "predictable" are not meant to...,” whereby where respondents may judge the conjunction of two events (that is, both A and B occurring) as more probability than the occurrence of just one of the two events, which contracts one of the basic axioms of logic (A and B cannot be more likely than “A or B”).
You can find examples of base rate neglect in this glossary entry on Bayes’ Theorem and Base Rate NeglectBayes' theorem refers to a probabilistic framework for updating beliefs in light of new evidence. Initially derived from the work of the Reverend (and statistician.... The most famous (and controversial) example of the conjunction fallacy is “the Linda problem,” described in this Wikipedia entry. Good examples of the “law of small numbers” point to the fact that people (or at least my students and others who have been given this task) asked to predict the sequence of coin flips with a fair coin tend to estimate it will oscillate between heads and tails far more systematically that it in fact does and, alternatively, will take a small series of all heads or all tails as more indicative of a biased coin than it in fact is. This, in turn, has been used in part to explain the hot hand cognitive illusion in basketball.