Symmetry, invariance and ontology in physics and statistics
type: Item
instance of: scholarly article
title: Symmetry, invariance and ontology in physics and statistics
zbMATH Open document ID: 1360.00084
author: Julio Michael Stern
published in: Symmetry
publication date: 2017-05-12T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 00A30
Mathematics Subject Classification ID: 03A05
zbMATH DE Number: 6714461
zbMATH Keywords: cognitive constructivism
zbMATH Keywords: de Finetti's and Noether's theorems
zbMATH Keywords: information geometry
zbMATH Keywords: MaxEnt formalism
zbMATH Keywords: objective ontologies
zbMATH Keywords: reference priors
zbMATH Keywords: subjectivism
describes a project that uses: BayesDA
MaRDI profile type: Publication
full work available at URL: sym3030611
OpenAlex ID: W2128895892
DOI: 10.3390/SYM3030611
description: scientific article; zbMATH DE number 6714461