统计推断原理

出版时间：2009-8  出版社：人民邮电出版社  作者：考克斯  页数：219  
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前言

　　Most statistical work is concerned directly with the provision and implementa-tion of methods for study design and for the analysis and interpretation of data.The theory of statistics deals in principle with the general concepts underlyingall aspects of such work and from this perspective the formal theory of statisticalinference is but a part of that full theory. Indeed， from the viewpoint of indi-vidual applications， it may seem rather a small part. Concern is likely to be moreconcentrated on whether models have been reasonably formulated to addressthe most fruitful questions， on whether the data are subject to unappreciatederrors or contamination and， especially， on the subject-matter interpretation ofthe analysis and its relation with other knowledge of the field.　　Yet the formal theory is important for a number of reasons. Without somesystematic structure statistical methods for the analysis of data become a col-lection of tricks that are hard to assimilate and interrelate to one another， orfor that matter to teach. The development of new methods appropriate for newproblems would become entirely a matter of ad hoc ingenuity. Of course suchingenuity is not to be undervalued and indeed one role of theory is to assimilate，generalize and perhaps modify and improve the fruits of such ingenuity.　　Much of the theory is concerned with indicating the uncertainty involved inthe conclusions of statistical analyses， and with assessing the relative merits ofdifferent methods of analysis， and it is important even at a very applied level tohave some understanding of the strengths and limitations of such discussions.This is connected with somewhat more philosophical issues connected withthe nature of probability. A final reason， and a very good one， for study of thetheory is that it is interesting.　　The object of the present book is to set out as compactly as possible thekey ideas of the subject， in particular aiming to describe and compare the mainideas and controversies over more foundational issues that have rumbled on atvarying levels of intensity for more than 200 years.

内容概要

本书是统计学名家名作，包含9章内容和两个附录，前面几章介绍一些基本概念，如参数、似然、主元等，然后介绍显著性检验、渐进理论以及比较复杂的统计推断问题。还特别介绍了实验设计中基于随机化的统计推断。核心概念的解释非常清晰，即使跳过其中的数学细节，也能使读者理解。    本书可作为工科、管理类学科专业本科生、研究生的教材或参考书，也可供教师、工程技术人员自学之用。

作者简介

　　D.R.Cox，世界著名统计学家，英国皇家学会会员暨英国社会科学院院士，美国科学院、丹麦皇家科学院外籍院士。曾任国际统计协会、伯努利数理统汁与概率学会、英国皇家统计学会主席。主要学术贡献包括Cox过程和影响深远且应用广泛的Cox比例风险模型等。

书籍目录

1　Preliminaries　Summary　1.1  Starting point　1.2  Role of formal theory of inference　1.3  Some simple models　1.4  Formulation of objectives　1.5  Two broad approaches to statistical inference　1.6  Some further discussion　1.7  Parameters　Notes 12　Some concepts and simple applications　Summary　2.1  Likelihood　2.2  Sufficiency　2.3  Exponential family　2.4  Choice of priors for exponential family problems　2.5  Simple frequentist discussion　2.6  Pivots　Notes 23　Significance tests　Summary　3.1  General remarks　3.2  Simple significance test　3.3  One- and two-sided tests　3.4  Relation with acceptance and rejection　3.5  Formulation of alternatives and test statistics　3.6  Relation with interval estimation　3.7  Interpretation of significance tests　3.8  Bayesian testing　Notes 34　More complicated situations　Summary　4.1  General remarks　4.2  General Bayesian formulation　4.3  Frequentist analysis　4.4  Some more general frequentist developments　4.5  Some further Bayesian examples　Notes 45　Interpretations of uncertainty　Summary　5.1  General remarks　5.2  Broad roles of probability　5.3  Frequentist interpretation of upper limits　5.4  Neyman-Pearson operational criteria　5.5  Some general aspects of the frequentist approach　5.6  Yet more on the frequentist approach　5.7  Personalistic probability　5.8  Impersonal degree of belief　5.9  Reference priors　5.10 Temporal coherency　5.11 Degree of belief and frequency　5.12 Statistical implementation of Bayesian analysis　5.13 Model uncertainty　5.14 Consistency of data and prior　5.15 Relevance of frequentist assessment　5.16 Sequential stopping　5.17 A simple classification problem　Notes 56　Asymptotic theory　Summary　6.1  General remarks　6.2  Scalar parameter　……7　Further aspects of maximum likelihood8　Additional objectives9　Randomization-based analysis

媒体关注与评论

　　“这是伟大统计学家的伟大著作。千万不能错过！　　——Ronaid Christensen。Journal of the American StatisticaI Association　　“本书是现代统计学之父的力作，深入阐述了统计推断的内容，行文流畅、语言优美。对所有从事统计工作的人来说，本书不可不读。”　　——Davtd Hand（伦敦大学帝国学院）　　“非常优秀的一本教材，在频率学派和贝叶斯学派之间找到了绝好的平衡，给出不偏不倚的观点。”　　——《应用统计》杂志

用户评论 (总计5条)

•   非常好的统计教材，只是书中很多细节缺失，大概是因为作者主要想介绍统计思想而非技术方法，所以对于基础比较差的读者需要配合一些其他教材来看~
•   统计是最精确的学科 我开始同意这个说法 并且深深地相信了
•   这书印的质量不太好，内容还好
•   好书，太棒了
•   给孩子买的书，挺满意的。