Chapman & hall/crc texts in statistical science - 9780367139919 - statistical rethinking: a bayesian course with examples in r and stan (chapman & hall/crc texts in statistical science) von mcelreath, richard (16 Ergebnisse)
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Sprache: Englisch
Verlag: Chapman and Hall/CRC (edition 2), 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
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Sprache: Englisch
Verlag: Chapman and Hall/CRC (edition 2), 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Hardcover. Zustand: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Hardcover. Zustand: Fine.
Sprache: Englisch
Verlag: CRC Press, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
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Sprache: Englisch
Verlag: CRC Press, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
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Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
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Zustand: New. In English.
Sprache: Englisch
Verlag: Chapman and Hall/CRC, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Statistical Rethinking
Richard McElreath (Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany)
Sprache: Englisch
Verlag: CRC Press, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Gebunden. Zustand: New. Richard McElreath studies human evolutionary ecology and is a Director at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. He has published extensively on the mathematical theory and statistical analysis of soc.
Sprache: Englisch
Verlag: Taylor & Francis Mär 2020, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Buch. Zustand: Neu. Neuware - Winner of the 2023 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based st…atistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work.The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding.The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new edition also contains new material on the design of prior distributions, splines, ordered categorical predictors, social relations models, cross-validation, importance sampling, instrumental variables, and Hamiltonian Monte Carlo. It ends with an entirely new chapter that goes beyond generalized linear modeling, showing how domain-specific scientific models can be built into statistical analyses.Features - Integrates working code into the main text. - Illustrates concepts through worked data analysis examples. - Emphasizes understanding assumptions and how assumptions are reflected in code. - Offers more detailed explanations of the mathematics in optional sections. - Presents examples of using the dagitty R package to analyze causal graphs. - Provides the rethinking R package on the author's website and on GitHub.
Sprache: Englisch
Verlag: Chapman & Hall, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Hardcover. Zustand: Brand New. 2nd edition. 593 pages. 10.50x7.50x1.25 inches. In Stock.
Sprache: Englisch
Verlag: Taylor & Francis Ltd, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Zustand: New. 2020. 2nd Edition. Hardcover. . . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Taylor & Francis, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Buch. Zustand: Neu. Statistical Rethinking | A Bayesian Course with Examples in R and STAN | Richard Mcelreath | Buch | Einband - fest (Hardcover) | Englisch | 2020 | Taylor & Francis | EAN 9780367139919 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: Taylor & Francis Mär 2020, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Buch. Zustand: Neu. Neuware -Winner of the 2023 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based sta…tistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work.The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding.The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new edition also contains new material on the design of prior distributions, splines, ordered categorical predictors, social relations models, cross-validation, importance sampling, instrumental variables, and Hamiltonian Monte Carlo. It ends with an entirely new chapter that goes beyond generalized linear modeling, showing how domain-specific scientific models can be built into statistical analyses.Features - Integrates working code into the main text. - Illustrates concepts through worked data analysis examples. - Emphasizes understanding assumptions and how assumptions are reflected in code. - Offers more detailed explanations of the mathematics in optional sections. - Presents examples of using the dagitty R package to analyze causal graphs. - Provides the rethinking R package on the author's website and on GitHub.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.
Sprache: Englisch
Verlag: Taylor & Francis Mär 2020, 2020
Serie: Buch 71 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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Buch. Zustand: Neu. Neuware -Winner of the 2023 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based sta…tistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work.The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding.The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new edition also contains new material on the design of prior distributions, splines, ordered categorical predictors, social relations models, cross-validation, importance sampling, instrumental variables, and Hamiltonian Monte Carlo. It ends with an entirely new chapter that goes beyond generalized linear modeling, showing how domain-specific scientific models can be built into statistical analyses.Features - Integrates working code into the main text. - Illustrates concepts through worked data analysis examples. - Emphasizes understanding assumptions and how assumptions are reflected in code. - Offers more detailed explanations of the mathematics in optional sections. - Presents examples of using the dagitty R package to analyze causal graphs. - Provides the rethinking R package on the author's website and on GitHub. Englisch.
