Daniel Kahneman and Amos Tversky have proposed that when judging the probability of some uncertain event people often resort to heuristics, or rules of thumb, which are less than perfectly correlated (if, indeed, at all) with the variables that actually determine the event's probability. One such heuristic is representativeness, defined as a subjective judgment of the extent to which the event in question “is similar in essential properties to its parent population” or “reflects the salient features of the process by which it is generated” (Kahneman & Tversky, 1972b, p. 431, 3). Although in some cases more probable events also appear more representative, and vice versa, reliance on the representativeness of an event as an indicator of its probability may introduce two kinds of systematic error into the judgment. First, it may give undue influence to variables that affect the representativeness of an event but not its probability. Second, it may reduce the importance of variables that are crucial to determining the event's probability but are unrelated to the event's representativeness.

The representativeness concept has occasionally been criticized as too vague and elusive, presumably because it lacks a general operational definition. This is not to say, however, that it is impossible to assess representativeness independently of probability judgments, a conclusion which has often been implied by the critics.