Languages and designs for probability judgment

Glenn Shafer; Amos Tversky

doi:10.1016/S0364-0213(85)80002-1

Languages and designs for probability judgment

Glenn Shafer
, Amos Tversky

Research output: Contribution to journal › Article › peer-review

142 Scopus citations

Abstract

Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability langauges, the Bayesian language and the language of belief functions (Shafer, 1976). We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.

Original language	English (US)
Pages (from-to)	309-339
Number of pages	31
Journal	Cognitive Science
Volume	9
Issue number	3
DOIs	https://doi.org/10.1016/S0364-0213(85)80002-1
State	Published - 1985
Externally published	Yes

All Science Journal Classification (ASJC) codes

Experimental and Cognitive Psychology
Cognitive Neuroscience
Artificial Intelligence

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10.1016/S0364-0213(85)80002-1

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title = "Languages and designs for probability judgment",

abstract = "Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability langauges, the Bayesian language and the language of belief functions (Shafer, 1976). We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.",

author = "Glenn Shafer and Amos Tversky",

note = "Funding Information: l This research has been supported in part by NSF grants MCS-800213 and 8301282 to the first author and by ONR Grant NR197-058 to the second author. The article has benefited from the comments of Jonathan Baron, Morris DeGroot, Persi Diaconis and David Krantz. Correspondence and requests for reprints should be sent to Glenn Shafer at the School of Business, University of Kansas, Lawrence, KS 66045.",

year = "1985",

doi = "10.1016/S0364-0213(85)80002-1",

language = "English (US)",

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pages = "309--339",

journal = "Cognitive Science",

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AU - Shafer, Glenn

AU - Tversky, Amos

N1 - Funding Information: l This research has been supported in part by NSF grants MCS-800213 and 8301282 to the first author and by ONR Grant NR197-058 to the second author. The article has benefited from the comments of Jonathan Baron, Morris DeGroot, Persi Diaconis and David Krantz. Correspondence and requests for reprints should be sent to Glenn Shafer at the School of Business, University of Kansas, Lawrence, KS 66045.

PY - 1985

Y1 - 1985

N2 - Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability langauges, the Bayesian language and the language of belief functions (Shafer, 1976). We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.

AB - Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability langauges, the Bayesian language and the language of belief functions (Shafer, 1976). We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.

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UR - https://www.scopus.com/pages/publications/0000241667#tab=citedBy

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DO - 10.1016/S0364-0213(85)80002-1

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SN - 0364-0213

VL - 9

SP - 309

EP - 339

JO - Cognitive Science

JF - Cognitive Science

IS - 3

ER -

Languages and designs for probability judgment

Abstract

All Science Journal Classification (ASJC) codes

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