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August 1998 Logicist statistics. I. Models and modeling
A. P. Dempster
Statist. Sci. 13(3): 248-276 (August 1998). DOI: 10.1214/ss/1028905887


Arguments are presented to support increased emphasis on logical aspects of formal methods of analysis, depending on probability in the sense of R. A. Fisher. Formulating probabilistic models that convey uncertain knowledge of objective phenomena and using such models for inductive reasoning are central activities of individuals that introduce limited but necessary subjectivity into science. Statistical models are classified into overlapping types called here empirical, stochastic and predictive, all drawing on a common mathematical theory of probability, and all facilitating statements with logical and epistemic content. Contexts in which these ideas are intended to apply are discussed via three major examples.


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A. P. Dempster. "Logicist statistics. I. Models and modeling." Statist. Sci. 13 (3) 248 - 276, August 1998.


Published: August 1998
First available in Project Euclid: 9 August 2002

zbMATH: 1099.62501
MathSciNet: MR1665717
Digital Object Identifier: 10.1214/ss/1028905887

Primary: 62A99

Keywords: complementarity , empirical, stochastic and predictive models , formal and informal , formal subjective probability , global climate change , Logicism and proceduralism , screening for chronic disease , specificity of analysis , subjective and objective , U.S. national census

Rights: Copyright © 1998 Institute of Mathematical Statistics


Vol.13 • No. 3 • August 1998
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