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The underinformative formulation of conditional probability

Published online by Cambridge University Press:  29 October 2007

Laura Macchi  and
Maria Bagassi
Laura Macchi
Affiliation:
Department of Psychology, University of Milano-Bicocca, 20126 Milan, Italy. laura.macchi@unimib.itmaria.bagassi@unimib.it
Maria Bagassi
Affiliation:
Department of Psychology, University of Milano-Bicocca, 20126 Milan, Italy. laura.macchi@unimib.itmaria.bagassi@unimib.it
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Abstract

The formulation of the conditional probability in classical tasks does not guarantee the effective transmission of the independence of the hit rate from the base rate. In these kinds of tasks, data are all available, but subjects are able to understand them in the specific meanings proper to a specialized language only if these are adequately transmitted. From this perspective, the partitive formulation should not be considered a facilitation, but rather, a way of effectively transmitting the conditional probability.

Consider the following two phrases:

  1. 1 The death-rate among men is twice that for women.

  2. 2 In the deaths registered last month there were twice as many men as women.

Are these two different ways of saying the same or are these different events? In fact, they are different events. (Lindley 1985, p. 44)

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 30 , Issue 3 , June 2007 , pp. 274 - 275
Copyright
Copyright © Cambridge University Press 2007

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References

Birnbaum, M. H. (1983) Base rates in Bayesian inference: Signal detection analysis of the cab problem. American Journal of Psychology 96:85–94.CrossRefGoogle Scholar
Dawes, R. M. (1988) Rational choice in an uncertain world. Harcourt Brace Jovanovich.Google Scholar
Girotto, V. & Gonzalez, M. (2001) Solving probabilistic and statistical problems: A matter of information structure and question form. Cognition 78:247–76.CrossRefGoogle ScholarPubMed
Grice, H. P. (1975) Logic and conversation. In: Syntax and semantics: Vol. 3. Speech acts, ed Cole, P. & Morgan, J. L..Academic Press.Google Scholar
Levinson, S. C. (1995) Interactional biases in human thinking. In: Social intelligence and interaction, ed Goody, E..Cambridge University Press.Google Scholar
Larkin, J. H. & Simon, H. A. (2000) Presumptive meanings. MIT Press.Google Scholar
Lindley, D. V. (1985) Making decisions. Wiley.Google Scholar
Macchi, L. (1995) Pragmatic aspects of the base rate fallacy. The Quarterly Journal of Experimental Psychology 48 A(1):188–207.CrossRefGoogle Scholar
Macchi, L. (2000) Partitive formulation of information in probabilistic problems: Beyond heuristics and frequency format explanations. Organizational Behavior and Human Decision Processes 82:217–36.CrossRefGoogle ScholarPubMed
Macchi, L. (2003) The partitive conditional probability. In: Thinking: Psychological perspectives on reasoning, judgment and decision making, ed Hardman, D. & Macchi, L., pp. 165–87. Wiley.CrossRefGoogle Scholar
Macchi, L., Bagassi, M. & Ciociola, P. B. (2007) The pragmatic approach versus the dual-process theories on probabilistic reasoning. (Unpublished manuscript.)Google Scholar
Macchi, L. & Mosconi, G. (1998) Computational features vs frequentist phrasing in the base-rate fallacy. Swiss Journal of Psychology 57:79–85.Google Scholar
Stanovich, K. E.West, R. F. (2000) Individual differences in reasoning: Implications for the rationality debate. Behavioral and Brain Sciences 23:645–726.CrossRefGoogle ScholarPubMed