如果你想学习贝叶斯计量经济学，这本是最好的入门读物，门槛较低，而且intuition讲得特别好。顺便的，你把R也学好了。
论坛上有第一版，这是今年十一月十七日Amazon上市的最新第二版，比起第一版有很多重大的改进，介绍见这本书的主页：
https://sites.google.com/site/doingbayesiandataanalysis/what-s-new-in-2nd-ed
看不到不是我的错，自己想办法埃

欢迎学习贝叶斯的同学一起交流！不要怕读英文书，多读就好了。

出版社高清原版，全网首发。喜欢的人记得给好评啊！

不缺论坛币，但是也不想这书在网上滥传，所以定价较高，只和真心想要学习的人分享。如何证明你的真心呢，暂时没别的交易成本较低的好办法，不好意思，只好还是用是否愿意付论坛币来衡量啦。



介绍引用Amazon：
Review"fills a gaping hole in what is currently available, and will serve to create its own market” Prof. Michael Lee, U. of Cal., Irvine; pres. Society for Mathematical Psych. "has the potential to change the way most cognitive scientists and experimental psychologists approach the planning and analysis of their experiments" Prof. Geoffrey Iverson, U. of Cal., Irvine; past pres. Society for Mathematical Psych. "better than others for reasons stylistic.... buy it -- it's truly amazin'!” James L. (Jay) McClelland, Lucie Stern Prof. & Chair, Dept. of Psych., Stanford U. "the best introductory textbook on Bayesian MCMC techniques" J. of Mathematical Psych. "potential to change the methodological toolbox of a new generation of social scientists" J. of Economic Psych. "revolutionary" British J. of Mathematical and Statistical Psych. "writing for real people with real data. From the very first chapter, the engaging writing style will get readers excited about this topic" PsycCritiques


From the Back CoverThere 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, correlation, 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.


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