出版社: Academic Press
副标题: A Tutorial with R and BUGS
原作名: John K. Kruschke
出版年: 2010-11-25
页数: 672
定价: GBP 64.48
装帧: Hardcover
ISBN: 9780123814852
内容简介 · · · · · ·
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book b...
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data. The text delivers comprehensive coverage of all scenarios addressed by non-Bayesian textbooks--t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). This book is intended for first year graduate students or advanced undergraduates. It provides a bridge between undergraduate training and modern Bayesian methods for data analysis, which is becoming the accepted research standard. Prerequisite is knowledge of algebra and basic calculus. Author website: http://www.indiana.edu/~kruschke/DoingBayesianDataAnalysis/
-Accessible, including the basics of essential concepts of probability and random sampling -Examples with R programming language and BUGS software -Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). -Coverage of experiment planning -R and BUGS computer programming code on website -Exercises have explicit purposes and guidelines for accomplishment
作者简介 · · · · · ·
John K. Kruschke is Professor of Psychological and Brain Sciences, and Adjunct Professor of Statistics, at Indiana University in Bloomington, Indiana, USA. He is eight-time winner of Teaching Excellence Recognition Awards from Indiana University. He won the Troland Research Award from the National Academy of Sciences (USA), and the Remak Distinguished Scholar Award from Indiana...
John K. Kruschke is Professor of Psychological and Brain Sciences, and Adjunct Professor of Statistics, at Indiana University in Bloomington, Indiana, USA. He is eight-time winner of Teaching Excellence Recognition Awards from Indiana University. He won the Troland Research Award from the National Academy of Sciences (USA), and the Remak Distinguished Scholar Award from Indiana University. He has been on the editorial boards of various scientific journals, including Psychological Review, the Journal of Experimental Psychology: General, and the Journal of Mathematical Psychology, among others.
After attending the Summer Science Program as a high school student and considering a career in astronomy, Kruschke earned a bachelor's degree in mathematics (with high distinction in general scholarship) from the University of California at Berkeley. As an undergraduate, Kruschke taught self-designed tutoring sessions for many math courses at the Student Learning Center. During graduate school he attended the 1988 Connectionist Models Summer School, and earned a doctorate in psychology also from U.C. Berkeley. He joined the faculty of Indiana University in 1989. Professor Kruschke's publications can be found at his Google Scholar page. His current research interests focus on moral psychology.
Professor Kruschke taught traditional statistical methods for many years until reaching a point, circa 2003, when he could no longer teach corrections for multiple comparisons with a clear conscience. The perils of p values provoked him to find a better way, and after only several thousand hours of relentless effort, the 1st and 2nd editions of Doing Bayesian Data Analysis emerged.
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0 有用 蝉 2013-11-04 18:53:47
:无
0 有用 lAxxx 2014-05-03 20:13:47
偏传统统计
0 有用 Samle 2014-09-29 00:40:11
this book has so many strange terms... perhaps the author is a psychologist.
1 有用 大橘为重 2015-08-05 00:39:26
简单生动,并且配上代码
1 有用 濯希 2019-03-27 09:20:18
贝叶斯极端主义者。讲解方式跟封面一样另类, 喜欢的人喜欢, 但很多人应该不能接受, 我就是不太能接受的那一类...
2 有用 1A7489 2019-06-13 03:51:43
更新:豆瓣书评群魔乱舞。Dr. Kruschke本人的确是Bayesian死忠,但他1、不是极端主义者2、不是左倾主义者,左倾这个词是说政治倾向的,不懂不要乱用。更有甚者说这本书的内容偏过去的传统统计?Bayesian上世纪70年代就有了知道吗?那叫frequentist不叫传统!书的第一章给你讲frequentist是怕你不懂基本概念带你复习,这怕是只看了第一章就胡扯 力荐给缺乏足够统计基础(如... 更新:豆瓣书评群魔乱舞。Dr. Kruschke本人的确是Bayesian死忠,但他1、不是极端主义者2、不是左倾主义者,左倾这个词是说政治倾向的,不懂不要乱用。更有甚者说这本书的内容偏过去的传统统计?Bayesian上世纪70年代就有了知道吗?那叫frequentist不叫传统!书的第一章给你讲frequentist是怕你不懂基本概念带你复习,这怕是只看了第一章就胡扯 力荐给缺乏足够统计基础(如非stats专业 bachelor)的初学者。Dr. Kruschke自己有blog,会经常在上面回答(书中提到的)问题和深入讨论。 使用的软件是R,主要算法集中在Gibbs Sampler方面,对HMC没有太多介绍。 另读完之后想要完全独立做Bayesian,还是要回去吃下Gelman的教材 (展开)
1 有用 濯希 2019-03-27 09:20:18
贝叶斯极端主义者。讲解方式跟封面一样另类, 喜欢的人喜欢, 但很多人应该不能接受, 我就是不太能接受的那一类...
1 有用 大橘为重 2015-08-05 00:39:26
简单生动,并且配上代码
0 有用 starsailor 2015-04-18 06:41:01
一本打着赌场掷骰子法则做幌子的科学书籍,封面可以不要卖萌么
0 有用 Samle 2014-09-29 00:40:11
this book has so many strange terms... perhaps the author is a psychologist.