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Introduction to Bayesian Statistics by Bolstad, William M., Curran, James M.
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- Buy It NowIntroduction to Bayesian Statistics by Bolstad, William M., Curran, James M.
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Item specifics
- Condition
- Book Title
- Introduction to Bayesian Statistics
- ISBN
- 9781118091562
- Subject Area
- Mathematics
- Publication Name
- Introduction to Bayesian Statistics
- Publisher
- Wiley & Sons, Incorporated, John
- Item Length
- 9.2 in
- Subject
- Probability & Statistics / General, Probability & Statistics / Bayesian Analysis
- Publication Year
- 2016
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 1.4 in
- Item Weight
- 34.1 Oz
- Item Width
- 6.1 in
- Number of Pages
- 624 Pages
About this product
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1118091566
ISBN-13
9781118091562
eBay Product ID (ePID)
228598770
Product Key Features
Number of Pages
624 Pages
Publication Name
Introduction to Bayesian Statistics
Language
English
Publication Year
2016
Subject
Probability & Statistics / General, Probability & Statistics / Bayesian Analysis
Type
Textbook
Subject Area
Mathematics
Format
Hardcover
Dimensions
Item Height
1.4 in
Item Weight
34.1 Oz
Item Length
9.2 in
Item Width
6.1 in
Additional Product Features
Edition Number
3
Intended Audience
Scholarly & Professional
LCCN
2017-385991
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
519.542
Synopsis
"...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the books related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the books website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics., "...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics., There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition , four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computational Bayesian Statistics including Markov Chain Monte Carlo methods. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. WinBUGS is discussed briefly in the coverage of Markov Chain Monte Carlo methods, and MiniTab macros and R functions are available on the book's related Web site to assist with chapter exercises., . this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible.|9781118091562|
LC Classification Number
QA279.5.B65 2016
Item description from the seller
Seller feedback (2,026)
- s***r (54)- Feedback left by buyer.Past 6 monthsVerified purchaseThe price was perfectly reasonable for the product, and the book arrived promptly and in great condition—like new, as described: the slightest bit of noticeable use and that was it. The seller wrapped it in literally 6 layers of protection (cardboard, bubble wrap, waterproof, etc.), which seemed like overkill but was much appreciated. My wife was so impressed that she demanded I leave a positive review immediately—and she was right. I’d be happy to do business with this seller again.
- m***_ (377)- Feedback left by buyer.Past 6 monthsVerified purchaseThe seller shipped the book quickly, tracked for added security and it arrived on time. Around 3 weeks which isn't bad at all. The book was exactly as advertised by the seller. I had no problem comunicating with the seller, he answered all my questions. He also packed the book very well so it wouldn't get damaged during shipping. It arrived as good as new. I'm very satisfied, the seller showed a very customer friendly /professional attitude. Hence my 5/5 positive feedback to him.Engineering a Compiler by Linda Torczon and Keith Cooper (2011, Hardcover) (#176727972484)
- a***4 (55)- Feedback left by buyer.Past 6 monthsVerified purchasePerfect shipping. My package came through with great timing, Everything looked exactly like it did in the previous description. Also the seller did an excellent job! Using good wrapping solution to make sure nothing got damaged, and I really do enjoy my package 📦 that was sent so most definitely recommend anyone who’s looking for something classic movie wise or tv series etc. To check out what great offers you will get to receive, rest assured that you will certainly not be disappointed.
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