1997/06/18 by O. A. Al-Hujaj, O. -A. Al-Hujaj, Al-Hujaj, O. -A. +2
Arts and Humanities · Physics and Astronomy · #Data Analysis #FOS: Physical sciences #Philosophy and History of Science #Quantum Mechanics and Applications #Statistical Mechanics and Entropy #Statistics and Probability (physics.data-an) #physics.data-an
paper · pdf · doi:10.48550/arxiv.physics/9706025
8 pages, RevTeX, 1 figure submitted to Phys. Rev. Let
arxiv created 1997/06/18 · openalex publication_date 1997/06/18 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Bayesian inference --- although becoming popular in physics and chemistry --- is hampered up to now by the vagueness of its notion of prior probability. Some of its supporters argue that this vagueness is the unavoidable consequence of the subjectivity of judgements --- even scientific ones. We argue that priors can be defined uniquely if the statistical model at hand possesses a symmetry and if the ensuing confidence intervals are subjected to a frequentist criterion. Moreover, it is shown via an example taken from recent experimental nuclear physics, that this procedure can be extended to models with broken symmetry.