Bayesian Ideas and Data Analysis - Christensen, Ronald; Johnson, Wesley; Branscum, Adam; Hanson, Timothy E
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Introducing Bayesian methods, this book emphasizes that the primary role of statistics is to provide appropriate tools for addressing scientific questions. As such, the authors present a collaborative approach to data analysis involving both scientists and statisticians that can be used to model unknown parameters using scientific information, called prior information or apriori. Keeping the mathematics to a minimum, the text focuses on applications, statistical ideas, models, and interpretations. It features WinBUGS throughout the computational problems and uses Monte Carlo methods for all simulations.…mehr

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Produktbeschreibung
Introducing Bayesian methods, this book emphasizes that the primary role of statistics is to provide appropriate tools for addressing scientific questions. As such, the authors present a collaborative approach to data analysis involving both scientists and statisticians that can be used to model unknown parameters using scientific information, called prior information or apriori. Keeping the mathematics to a minimum, the text focuses on applications, statistical ideas, models, and interpretations. It features WinBUGS throughout the computational problems and uses Monte Carlo methods for all simulations.
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Autorenporträt
Ronald Christensen is a Professor in the Department of Mathematics and Statistics at the University of New Mexico, Albuquerque. He is also a Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics as well as the former Chair of the ASA Section on Bayesian Statistical Science. Wesley Johnson is a Professor in the Department of Statistics at the University of California, Irvine. He is also a Fellow of the ASA and Chair-Elect of the ASA Section on Bayesian Statistical Science. Adam Branscum is an Associate Professor in the Department of Public Health at Oregon State University, Corvallis. Timothy E. Hanson is an Associate Professor in the Department of Statistics at the University of South Carolina, Columbia.