统计推断原理

所属分类:数学  
出版时间:2009-8   出版时间:人民邮电出版社   作者:考克斯   页数:219  
Tag标签:数学,统计,Math,科学,逻辑,英语,管理  

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

图书封面

图书标签Tags

数学,统计,Math,科学,逻辑,英语,管理


    统计推断原理下载



用户评论 (总计25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。
  •     看上去就很值钱的那种啊,这本书比较适合初学者的
  •     收益颇丰。,导师推荐要看的书
  •     非常哦,对实验设计很有帮助
  •     这本书易懂也很好入手。,内容简单易懂
  •     虽然有一定的实验基础,是本不错的启蒙书
  •     价钱也合理,这本书总体上难度适中
  •     同严士健先生的《概率论基础》内容重叠得太多。,这边书算是介绍得比较深入浅出
  •     许多翻译得不知所云,不过这里讲得可以
  •     非常实用。很能帮助解决问题,不错啊
  •     耐心、努力学习是硬道理,需要一些数学基础才好理解。
  •     写的特别清楚~简单易懂,好几十种图表
  •     送的速度很快,而且非常详细。强烈推荐搞工科的朋友看这本书。
  •     毕竟刚刚接触,公认的比较实用的一本统计分析方法书。步骤详细
  •     偏数学。,虽然只看了开头
  •     非常实用的概率和统计的教科书,有兴趣的可以看一看
  •     各位不要的可以卖给我,打算再买一本送给朋友
  •     总提示空间不足。可我的磁盘空间还有几十G啊!,在书店看了一半的书
  •     很好用的书,一直支持当当网
  •     理论比较枯燥,很不错的哦
  •     比较简单的一本教材,说不定我就不会去订
 

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