Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem
Bertrand’s paradox is a problem in geometric probability that has resisted resolution for more than one hundred years. Bertrand provided three seemingly reasonable solutions to his problem — hence the paradox. Bertrand’s paradox has also been influential in philosophical debates about frequentist ve...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/15/3282 |
| _version_ | 1797586374915784704 |
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| author | Richard A. Chechile |
| author_facet | Richard A. Chechile |
| author_sort | Richard A. Chechile |
| collection | DOAJ |
| description | Bertrand’s paradox is a problem in geometric probability that has resisted resolution for more than one hundred years. Bertrand provided three seemingly reasonable solutions to his problem — hence the paradox. Bertrand’s paradox has also been influential in philosophical debates about frequentist versus Bayesian approaches to statistical inference. In this paper, the paradox is resolved (1) by the clarification of the primary variate upon which the principle of maximum entropy is employed and (2) by imposing constraints, based on a mathematical analysis, on the random process for any subsequent nonlinear transformation to a secondary variable. These steps result in a unique solution to Bertrand’s problem, and this solution differs from the classic answers that Bertrand proposed. It is shown that the solutions proposed by Bertrand and others reflected sampling processes that are not purely random. It is also shown that the same two steps result in the resolution of the Bing–Fisher problem, which has to do with the selection of a consistent prior for Bayesian inference. The resolution of Bertrand’s paradox and the Bing–Fisher problem rebuts philosophical arguments against the Bayesian approach to statistical inference, which were based on those two ostensible problems. |
| first_indexed | 2024-03-11T00:22:22Z |
| format | Article |
| id | doaj.art-580e48c5b50349e9a8e0df57709b2d83 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T00:22:22Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-580e48c5b50349e9a8e0df57709b2d832023-11-18T23:14:34ZengMDPI AGMathematics2227-73902023-07-011115328210.3390/math11153282Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher ProblemRichard A. Chechile0Psychology and Cognitive and Brain Science, Tufts University, Medford, MA 02155, USABertrand’s paradox is a problem in geometric probability that has resisted resolution for more than one hundred years. Bertrand provided three seemingly reasonable solutions to his problem — hence the paradox. Bertrand’s paradox has also been influential in philosophical debates about frequentist versus Bayesian approaches to statistical inference. In this paper, the paradox is resolved (1) by the clarification of the primary variate upon which the principle of maximum entropy is employed and (2) by imposing constraints, based on a mathematical analysis, on the random process for any subsequent nonlinear transformation to a secondary variable. These steps result in a unique solution to Bertrand’s problem, and this solution differs from the classic answers that Bertrand proposed. It is shown that the solutions proposed by Bertrand and others reflected sampling processes that are not purely random. It is also shown that the same two steps result in the resolution of the Bing–Fisher problem, which has to do with the selection of a consistent prior for Bayesian inference. The resolution of Bertrand’s paradox and the Bing–Fisher problem rebuts philosophical arguments against the Bayesian approach to statistical inference, which were based on those two ostensible problems.https://www.mdpi.com/2227-7390/11/15/3282Bertrand’s paradoxBing–Fisher problemphilosophical theories of probabilitynon-informative Bayesian priorJeffreys prior |
| spellingShingle | Richard A. Chechile Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem Mathematics Bertrand’s paradox Bing–Fisher problem philosophical theories of probability non-informative Bayesian prior Jeffreys prior |
| title | Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem |
| title_full | Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem |
| title_fullStr | Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem |
| title_full_unstemmed | Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem |
| title_short | Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem |
| title_sort | bertrand s paradox resolution and its implications for the bing fisher problem |
| topic | Bertrand’s paradox Bing–Fisher problem philosophical theories of probability non-informative Bayesian prior Jeffreys prior |
| url | https://www.mdpi.com/2227-7390/11/15/3282 |
| work_keys_str_mv | AT richardachechile bertrandsparadoxresolutionanditsimplicationsforthebingfisherproblem |