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Symmetry, Invariance and Ontology in Physics and Statistics

Stern, Julio Michael (2011) Symmetry, Invariance and Ontology in Physics and Statistics. Symmetry, 3 (3). pp. 611-635. ISSN 2073-8994

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Abstract

This paper has three main objectives: (a) Discuss the formal analogy between some important symmetry-invariance arguments used in physics, probability, and statistics. Specifically, we will focus on Noether’s theorem in physics, the maximum entropy principle in probability theory, and de Finetti-type theorems in Bayesian statistics; (b) Discuss the epistemological and ontological implications of these theorems, as they are interpreted in physics and statistics. Specifically, we will focus on the positivist (in physics) or subjective (in statistics) interpretations vs. objective interpretations that are suggested by symmetry and invariance arguments; (c) Introduce the cognitive constructivism epistemological framework as a solution that overcomes the realism-subjectivism dilemma and its pitfalls. The work of the physicist and philosopher Max Born will be particularly important in our discussion.


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Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Stern, Julio Michael0000-0003-2720-3871
Keywords: cognitive constructivism; de Finetti's and Noether's theorems; information geometry; MaxEnt formalism; objective ontologies; reference priors; subjectivism.
Subjects: General Issues > Confirmation/Induction
General Issues > Evidence
General Issues > Laws of Nature
Specific Sciences > Probability/Statistics
Depositing User: Prof. Julio Michael Stern
Date Deposited: 26 Mar 2023 18:25
Last Modified: 26 Mar 2023 18:25
Item ID: 21922
Journal or Publication Title: Symmetry
Official URL: http://doi.org/10.3390/sym3030611
DOI or Unique Handle: https://doi.org/10.3390/sym3030611
Subjects: General Issues > Confirmation/Induction
General Issues > Evidence
General Issues > Laws of Nature
Specific Sciences > Probability/Statistics
Date: 2011
Page Range: pp. 611-635
Volume: 3
Number: 3
ISSN: 2073-8994
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/21922

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