Introduction à la statistique bayésienne
Bayesian statistics is everywhere: weather forecasting, epidemic analysis, biodiversity conservation… In an uncertain world, it helps us estimate, predict, and make decisions by giving meaning to data. This book offers an accessible and practical introduction to Bayesian statistics. The author expla...
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| Materyal Türü: | Online |
| Dil: | Fransızca |
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éditions Quae
2026
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| Online Erişim: | ONIX_20260519T105719_9782759242573_4 |
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| _version_ | 1869521704741502976 |
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| author | Gimenez, Olivier |
| author_browse | Gimenez, Olivier |
| author_facet | Gimenez, Olivier |
| author_sort | Gimenez, Olivier |
| collection | Directory of Open Access Books |
| description | Bayesian statistics is everywhere: weather forecasting, epidemic analysis, biodiversity conservation… In an uncertain world, it helps us estimate, predict, and make decisions by giving meaning to data. This book offers an accessible and practical introduction to Bayesian statistics. The author explains, step-by-step, the fundations of the approach, its advantages, and the logic underlying Bayesian reasoning. Learning is built around the free software R and develops through research questions related to the ecology of the coypu, which serves as the book's guiding thread. Each chapter addresses a key pillar: Bayes' theorem, Markov chain Monte Carlo (MCMC) methods, the choice and role of prior distributions, linear regression and its extensions, generalized linear models (mixed or not), and finally model comparison and validation. Readers are invited to code, simulate, test, and visualize in order to understand, supported by worked examples and online materials. Written in a clear and engaging style, like a dialogue between teacher and student, the book demystifies Bayesian statistics. It is intended for anyone wishing to learn this approach, particularly those working in the life sciences, data science, or environmental sciences. |
| format | Online |
| id | doab-20.500.12854ir-176711 |
| institution | Directory of Open Access Books |
| language | fre |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | éditions Quae |
| publisherStr | éditions Quae |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1767112026-05-20T08:49:42Z Introduction à la statistique bayésienne Gimenez, Olivier Bayesian statistics Ecology Bayes' theorem Monte Carlo methods R software Brms thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPS Research methods: general thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics Bayesian statistics is everywhere: weather forecasting, epidemic analysis, biodiversity conservation… In an uncertain world, it helps us estimate, predict, and make decisions by giving meaning to data. This book offers an accessible and practical introduction to Bayesian statistics. The author explains, step-by-step, the fundations of the approach, its advantages, and the logic underlying Bayesian reasoning. Learning is built around the free software R and develops through research questions related to the ecology of the coypu, which serves as the book's guiding thread. Each chapter addresses a key pillar: Bayes' theorem, Markov chain Monte Carlo (MCMC) methods, the choice and role of prior distributions, linear regression and its extensions, generalized linear models (mixed or not), and finally model comparison and validation. Readers are invited to code, simulate, test, and visualize in order to understand, supported by worked examples and online materials. Written in a clear and engaging style, like a dialogue between teacher and student, the book demystifies Bayesian statistics. It is intended for anyone wishing to learn this approach, particularly those working in the life sciences, data science, or environmental sciences. 2026-05-20T08:49:37Z 2026-05-20T08:49:37Z 2026-05-19T12:38:16Z 2026 book ONIX_20260519T105719_9782759242573_4 https://library.oapen.org/handle/20.500.12657/113142 9782759242573 9782759242580 9782759242597 https://directory.doabooks.org/handle/20.500.12854/176711 fre Hors collection open access image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://library.oapen.org/bitstream/20.500.12657/113142/1/9782759242573.pdf éditions Quae 10.35690/978-2-7592-4258-0 10.35690/978-2-7592-4258-0 0a7aef96-655f-462d-9d9a-7da8417f35c0 9782759242573 9782759242580 9782759242597 78 Versailles open access |
| spellingShingle | Bayesian statistics Ecology Bayes' theorem Monte Carlo methods R software Brms thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPS Research methods: general thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics Gimenez, Olivier Introduction à la statistique bayésienne |
| title | Introduction à la statistique bayésienne |
| title_full | Introduction à la statistique bayésienne |
| title_fullStr | Introduction à la statistique bayésienne |
| title_full_unstemmed | Introduction à la statistique bayésienne |
| title_short | Introduction à la statistique bayésienne |
| title_sort | introduction a la statistique bayesienne |
| topic | Bayesian statistics Ecology Bayes' theorem Monte Carlo methods R software Brms thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPS Research methods: general thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics |
| topic_facet | Bayesian statistics Ecology Bayes' theorem Monte Carlo methods R software Brms thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPS Research methods: general thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics |
| url | ONIX_20260519T105719_9782759242573_4 |
| work_keys_str_mv | AT gimenezolivier introductionalastatistiquebayesienne |