Man as an intuitive statistician.

Peterson, Cameron R.; Beach, Lee Roy

doi:10.1037/h0024722

Cited by 861 publications

(459 citation statements)

References 78 publications

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“…[insert (Inhelder & Piaget, 1955/1958Smedslund, 1963;Peterson & Beach, 1967;McKenzie, 1994). A typical task involves two binary variables: X (e.g., glom or not) and Y McKenzie and Mikkelsen (in press) proposed that subjects may be approaching covariation assessment tasks as inferential tasks, and using their prior beliefs to interpret the tasks.…”

Section: Finding Useful Questions 15mentioning

confidence: 99%

“…Use of normative models as descriptive models, or to facilitate development of descriptive models, is a familiar research strategy (Anderson's 1990(Anderson's , 1991Brunswik's, 1952, molar analysis; Peterson & Beach, 1967;Marr, 1982;Viswanathan, et al, 1999;Oaksford & Chater, 2001;McKenzie, 2003;Baron, 2004). However, Kuhn (1989Kuhn ( , 2000 discusses both the usefulness and limitations of the normative intuitive scientist metaphor as a descriptive model of human cognition.…”

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confidence: 99%

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Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain.

Nelson

2005

Psychological Review

223

403

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Several norms for how people should assess a question's usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback-Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment, medical diagnosis, and the selection task are shown to not discriminate among these norms as descriptive models of human intuitions and behavior. Computational optimization found situations in which information gain, probability gain, and impact strongly contradict Bayesian diagnosticity. In these situations, diagnosticity's claims are normatively inferior. Results of a new experiment strongly contradict the predictions of Bayesian diagnosticity. Normative theoretical concerns also argue against use of diagnosticity. It is concluded that Bayesian diagnosticity is normatively flawed and empirically unjustified.

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Section: Finding Useful Questions 15mentioning

confidence: 99%

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confidence: 99%

Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain.

Nelson

2005

Psychological Review

223

403

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“…As Jones (1985) points out, "Asch solved the accuracy problem by bypassing it" (p. 87). Other psychologists interested in the process of social judgment, inspired by Heider (1958), concentrated on building idealized, normative models of the judgment process, such as the "correspondent inference theory" of Jones and Davis (1965), the "attributional cube" of Kelley (1967), and the more general work by Peterson and Beach (1967). These models emphasized the logical structure of judgment, and were based on the working assumption that people are perfectly "rational" processors of information.…”

Section: Evolution Of Research On Accuracy and Errormentioning

confidence: 99%

Errors and mistakes: Evaluating the accuracy of social judgment.

Funder¹

1987

Psychological Bulletin

800

461

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research on "error" in social judgment has largely supplanted research that addresses accuracy issues more directly. Moreover, this research attracts a great deal of attention because of what many take to be its dismal implications for the accuracy of human social reasoning. These implications are illusory, however, because an error is not the same thing as a "mistake." An error is a judgment of an experimental stimulus that departs from a model of the judgment process. If this model is normative, then the error can be said to represent an incorrect judgment. A mistake, by contrast, is an incorrect judgment of a real-world stimulus and therefore more difficult to determine. Although errors can be highly informative about the process of judgment in general, they are not necessarily relevant to the content or accuracy of particular judgments, because errors in a laboratory may not be mistakes with respect to a broader, more realistic frame of reference and the processes that produce such errors might lead to correct decisions and adaptive outcomes in real life. Several examples are described in this article. Accuracy issues cannot be addressed by research that concentrates on demonstrating error in relation to artificial stimuli, but only by research that uses external, realistic criteria for accuracy. These criteria might include the degree to which judgments agree with each other and yield valid predictions of behavior. The accuracy of human social judgment is a topic of obvious interest and importance. It is only natural to wonder to what degree the judgments we make of the personalities of ourselves and others might be right or wrong, and to desire to improve our accuracy. Nonpsychologists are often surprised and disappointed, therefore, when they begin to take psychology courses and discover that the field has largely foresworn interest in the accuracy issue. The discipline's early, direct interest in accuracy (e.g., Estes, 1938; Taft, 1955; Vernon, 1933) was all but completely stifled some years ago by the publication of a series of methodological critiques by Cronbach (1955), Hastorf and Bender (1952), and others. As a result, according to one authoritative textbook: The accuracy issue has all but faded from view in recent years, at least for personality judgments. There is not much present interest in questions about whether people are accurate... . There is, in short, almost no concern with normative questions of accuracy. On the other hand, in recent years there has been a renewed interest in how, why, and in what circumstances people are inaccurate. (Schneider, Hastorf, & Ellsworth, 1979, p. 224; see also Cook, 1984)' Specifically, the psychology of social judgment has been dominated in recent years by a flood of research on the subject of "error." Studies of error appear in the literature at a prodigious rate, are disproportionately likely to be cited (Christensen-Sza

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“…A decade later Wason (1966) extended the hypothesis to "deductive reasoning" and Peterson and Beach (1967) provided an alternative formulation for statistical inferences:…”

Section: Normative Manmentioning

confidence: 99%