Bayesian Ideas and Data Analysis (eBook)

An Introduction for Scientists and Statisticians
Artikelnummer: 978-1-4398-9151-3
Einband: Adobe Digital Editions
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to col

Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to col

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VerlagTaylor & Francis Ebooks
EinbandAdobe Digital Editions
Erscheinungsjahr2010
Seitenangabe516 S.
AusgabekennzeichenEnglisch
Abbildungen87 schwarz-weiße Abbildungen, 57 schwarz-weiße Tabellen
Auflage10001 A. 1. Auflage
PlattformEPUB
AutorChristensen, Ronald / Johnson, Wesley / Branscum, Adam / Hanson, Timothy E

Über den Autor Ronald Christensen

Ronald Christensen is a Distinguished Professor of Statistics at the University of New Mexico. He is well known for his work on the theory and application of statistical models having linear structure. In addition to numerous technical articles, he is the author of Plane Answers to Complex Questions: The Theory of Linear Models; Advanced Linear Modeling: Statistical Learning and Dependent Data; Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data and coauthor of Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians. Dr. Christensen is a fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics. His is a past editor of The American Statistician and a past chair of the ASA's Section on Bayesian Statistical Science.

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