贝叶斯方法是基于贝叶斯定理而发展起来用于系统地阐述和解决统计问题的方渚上用贝叶斯定理的方式依赖于一个统计学家如何看待“概率”的基本概念。这些统计学家“推崇”概率为不确定性的度量，对于任何实际客体它将会被认定；因此没有任何理由贝叶斯定理不在任何场合应用。本书的主要内容包括贝叶斯立场、先验分布，后验分布及贝叶斯推断、常用分布、可靠性问题、经验贝叶方法、贝叶斯统计地应用、参考文献。

The resources that statisticians use directly affect people, government and society. Opinion polls influence political opinion; statistical evidence supports medical advances. In the sixth edition of his groundbreaking text, David Moore emphasizes the concepts and applications of statistics from a wide range of fields - encouraging students to see the meaning behind statistical results whilst retaining their interest. Moore's emphasis on ideas and data with minimal computation is generally acknowledged as the most effective way to teach non-mathematical students.

统计学是论述收集. 分析并解释数

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.

《多元统计分析及R语言建模（第2版）》共分14章，主要内容有：多元数据的收集和整理、多元数据的直观显示、线性与非线性模型及广义线性模型、判别分析、聚类分析、主成分分析、因子分析、对应分析、典型相关分析等常见的主流方法。《多元统计分析及R语言建模（第2版）》还参考国内外大量文献，系统地介绍了这些年在经济管理等领域应用颇广的一些较新方法，可作为统计学专业本科生和研究生的多元分析课程教材。