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Irrational Numbers: Quantifying Accuracy and Error
DOI link for Irrational Numbers: Quantifying Accuracy and Error
Irrational Numbers: Quantifying Accuracy and Error book
Irrational Numbers: Quantifying Accuracy and Error
DOI link for Irrational Numbers: Quantifying Accuracy and Error
Irrational Numbers: Quantifying Accuracy and Error book
ABSTRACT
E xperimental psychologists thrive on deciencies. Consider just a handful of shortcomings that interest them: judgmental overcondence, the bet-ter-than-average effect, correspondence bias, the fundamental attribution error, conrmation bias, the planning fallacy, gambler’s fallacy, hindsight bias, egocentric bias, the sunk-costs fallacy, the illusion of control, omission bias, neglect bias, and on and on (see Jussim, Stevens, & Salib, this volume, Chapter 6; Krueger, this volume, Chapter 4). These phenomena differ from one another in substantive regards, but they share an important quality. Each points to ways in which social judgments can be systematically distorted away from a criterion of “accuracy” or “rationality” that is held up as an ideal in a theoretical model of human cognition. Such comparisons between actual judgments and idealized judgments pervade the psychological literature. At times, the idealized model has been explicated as the response that should be observed when people adhere to rational thought processes (for example, Jones & Davis, 1965; Kelley, 1967). Other times, it is adapted from statistical or mathematical models (for example, Tversky & Kahneman, 1971). Still other times, the ideal is so obviously the “correct” response that researchers merely appeal to the counterintuitive nature of a response (Prentice & Miller, 1992).