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Foundational Bayesian statistics for scientific applications.
If you're looking to understand the Bayesian perspective on statistics, particularly in scientific research, this book could be a goldmine for you. It takes complex ideas and makes them accessible, offering practical guidance on applying Bayesian methods to real data analysis. You'll appreciate the real-world examples that can crystalize abstract concepts.
Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
Sale
Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians
Regular price
₱2,700.00
Now ₱1,200.00
Save 56%
Compare to estimated retail price: ₱6,300.00 PHP
- Unit price
- / per
The item you've got your eye on is secondhand. You probably already know that, but just in case!
The estimated retail price shown next to any listed item represents the first-hand prices we've seen elsewhere, or the estimated original retail price of a comparable item of the same quality, construction and material offered elsewhere in new condition.
Save 41%
Save 56%
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ISBN: 9781439803547
Publisher: CRC Press
Date of Publication: 2010-07-02
Format: Hardcover
Goodreads rating: 3.89
(rated by 9 readers)
Description
Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis 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 collaborate in analyzing data. The WinBUGS code provided offers a convenient platform to model and analyze a wide range of data. The first five chapters of the book contain core material that spans basic Bayesian ideas, calculations, and inference, including modeling one and two sample data from traditional sampling models. The text then covers Monte Carlo methods, such as Markov chain Monte Carlo (MCMC) simulation. After discussing linear structures in regression, it presents binomial regression, normal regression, analysis of variance, and Poisson regression, before extending these methods to handle correlated data. The authors also examine survival analysis and binary diagnostic testing. A complementary chapter on diagnostic testing for continuous outcomes is available on the book’s website. The last chapter on nonparametric inference explores density estimation and flexible regression modeling of mean functions. The appropriate statistical analysis of data involves a collaborative effort between scientists and statisticians. Exemplifying this approach, Bayesian Ideas and Data Analysis focuses on the necessary tools and concepts for modeling and analyzing scientific data. Data sets and codes are provided on a supplemental.
Condition guide
Book Condition Guide
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This book may contain very minor cosmetic defects, but it is in pristine condition. There should be no yellowing, no foxing, no water damage, and no annotations of any kind on the cover and the pages. For paperbacks, there should not be any crease marks on the spine. This book is good as new — lucky you!
*Books may be missing bundle media (e.g. CD, e-book code), if included.
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*Books may be missing bundle media (e.g. CD, e-book code), if included.
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*Books may be missing bundle media (e.g. CD, e-book code), if included.
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Foundational Bayesian statistics for scientific applications.
If you're looking to understand the Bayesian perspective on statistics, particularly in scientific research, this book could be a goldmine for you. It takes complex ideas and makes them accessible, offering practical guidance on applying Bayesian methods to real data analysis. You'll appreciate the real-world examples that can crystalize abstract concepts.
Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.
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