The underinformative formulation of conditional probability

Behavioral and Brain Sciences 30 (3):274-275 (2007)
  Copy   BIBTEX

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

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 100,154

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

First things first: What is a base rate?Clark McCauley - 1996 - Behavioral and Brain Sciences 19 (1):33-34.
Implications of natural sampling in base-rate tasks.Gernot D. Kleiter - 2007 - Behavioral and Brain Sciences 30 (3):270-271.
Operating on functions with variable domains.Philip G. Calabrese - 2003 - Journal of Philosophical Logic 32 (1):1-18.
Pragmatically before ecologically valid tasks.Laura Macchi - 1997 - Behavioral and Brain Sciences 20 (4):778-779.
P(D/H), P(D/˜H), and base rate consideration.Yechiel Klar - 1996 - Behavioral and Brain Sciences 19 (1):26-27.
Centering and compound conditionals under coherence.A. Gilio, Niki Pfeifer & Giuseppe Sanfilippo - 2017 - In M. B. Ferraro, P. Giordani, B. Vantaggi, M. Gagolewski, P. Grzegorzewski, O. Hryniewicz & María Ángeles Gil (eds.), Soft Methods for Data Science. pp. 253-260.
Relational Quantum Mechanics and Probability.M. Trassinelli - 2018 - Foundations of Physics 48 (9):1092-1111.
Quantifier probability logic and the confirmation paradox.Theodore Hailperin - 2007 - History and Philosophy of Logic 28 (1):83-100.

Analytics

Added to PP
2009-01-28

Downloads
52 (#412,556)

6 months
9 (#455,691)

Historical graph of downloads
How can I increase my downloads?