《对数线性模型》是最好的对数线性模型教学材料之一，不仅讨论了一般对数线性模型，还讨论了logit模型，这一模型通过分析作为自变量函数的因变量的期望发生比来检验自变量与因变量之间的关系。作者从处理二分变量的方法开始，逐步形成一个处理多类别变量的方法。在理论阐述的过程中，作者还使用了大量的来源于政治社会学的例子，每个例子都阐明了对数线性模型的具体运用。最后，作者讨论了对数线性模型运用中的具体问题。

An exclusive insight -- by Fisher's daughter -- of a man whose achievements in mathematical statistics continue to dominate the age. Traces his mobilization and extension of the resources of mathematics to solve the problems of estimation, analysis and design of experiments, and inductive inference. Reflecting the vitality of Fisher's immense pleasure in the process of thinking, the play of ideas, and the solution of puzzles, this biography introduces a complex and fascinating personality.

The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes. In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.
In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jörn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.
* An irreverent review of econometric essentials
* A focus on tools that applied researchers use most
* Chapters on regression-discontinuity designs, quantile regression, and standard errors
* Many empirical examples
* A clear and concise resource with wide applications

社会研究的统计应用，ISBN：9787801494313，作者：李沛良著

一本针对研究生的讲述定量研究方法的教辅书，美国定量研究方法领域权威教授写就，针对中国国内“重定性，轻定量”的研究现状，就定量研究的本质、基础、范畴和争论，做了精辟的论述和分析，是国内外广大对社会科学方法研究有专长或有兴趣的学者和学生必备的手册和工具，正应时下社会科学研究之需。

Elementary set theory accustoms the students to mathematical abstraction, includes the standard constructions of relations, functions, and orderings, and leads to a discussion of the various orders of infinity. The material on logic covers not only the standard statement logic and first-order predicate logic but includes an introduction to formal systems, axiomatization, and model theory. The section on algebra is presented with an emphasis on lattices as well as Boolean and Heyting algebras. Background for recent research in natural language semantics includes sections on lambda-abstraction and generalized quantifiers. Chapters on automata theory and formal languages contain a discussion of languages between context-free and context-sensitive and form the background for much current work in syntactic theory and computational linguistics. The many exercises not only reinforce basic skills but offer an entry to linguistic applications of mathematical concepts. For upper-level undergraduate students and graduate students in theoretical linguistics, computer-science students with interests in computational linguistics, logic programming and artificial intelligence, mathematicians and logicians with interests in linguistics and the semantics of natural language

This text provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of moments, which is used to motivate a wide variety of estimators and tests. Simulation methods, including the bootstrap, are introduced early and used extensively. The book deals with a large number of modern topics. In addition to bootstrap and Monte Carlo tests, these include sandwich covariance matrix estimators, artificial regressions, estimating functions and the generalized method of moments, indirect inference, and kernel estimation. Every chapter incorporates numerous exercises, some theoretical, some empirical, and many involving simulation. Econometric Theory and Methods is designed for beginning graduate courses. The book is suitable for both one- and two-term courses at the Masters or Ph.D. level. It can also be used in a final-year undergraduate course for students with sufficient backgrounds in mathematics and statistics.

This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

《多层次模型》首先对社会与健康科学研究中的多层次模型统计方法做了一些相对非技术性的介绍。然后介绍了二层模型及其拟合方法，包括数据准备、模型估计、模型解释、假设检验、模型假设条件检验以及中心化。最后是对多层次模型的扩展应用，包括对非连续型因变量和非正态分布型因变量的处理，以及使用多层次方法分析纵向数据和构建三层模型。这些内容都讨论了其与多元回归的相似性，并且对例子中的数据和分析进行扩展运用。

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

《结构方程模型:AMOS的操作与应用(第2版)》前半部介绍结构方程模型（SEM）的概念与AmosGraphics窗口界面的基本操作；后半部以各种实例介绍AmosGraphics在各种SEM模型中的应用。全书采用AMOS图像界面，完全没有复杂的SEM理论推导和语法，最大的特点就是对利用AMOS进行结构方程模型各种分析的每一个步骤都有详细的讲解和图示。这是一本“使用者界面”取向的书籍，即使是不懂传统SEM语法使用者，也能在最短时间内学会用AMOS绘制各种SEM模型图，并将模型估计、模型识别判断、模型修正与模型验证，实际应用于自己的研究领域中。《结构方程模型:AMOS的操作与应用(第2版)》的读者对象是结构方程模型分析方法的学习者和使用者，适合社会科学各学科高年级本科生、硕博士研究生自学，也适合教师教学辅助参考。

您一直等待的修订版就在这里！由于充满丰富的研究示例，并对分层线性模型(HLM)理论与应用有透彻的解释，其第1版就广受欢迎，现在这本书的第2版又重新组织为四大部分，并且加入了全新的4章内容。前两个部分，即第一部分“原理”和第二部分“基本应用”，紧密对应着上一版中的9章，但是已经大量扩展了内容，技术解释更为清晰，比如：
对HLM模型中的基本估计和推断程序提供了一个直观的介绍性总结。
在第6章中新加了一节多元增长模型。
第7章增加了对研究综合或元分析应用的讨论。
对数据分析中层-1自变量定位方法的建议以及可信值区间与稳健标准误方面的新材料。
虽然第1版主要是讨论层-1结果变量为连续分布的情况，然而现在的第 2版的第三部分中又包括了一系列其他类型结果变量的分析，比如： 　　新的第10章介绍分层模型在结果变量为二分类变量、计数变量、序次变量以及多项分类变量条件下的应用，并且每种情况都提供了详细的示例和说明。
新的第11章讨论了潜在变量模型，其中包括在HLM框架下对有缺失的数据以及在自变量有测量误差时如何进行回归估计，还包括了嵌入性分项反应模型。
第13章则是关于分层数据分析中贝叶斯推断原理的介绍。
作者在第四部分中对全书应用的统计理论以及计算方法进行了总结，包括层-1为正态分布误差的单变量模型、多元线性模型以及分层一般化线性模型。此外，还给读者提供了一个新的链接网址，可以下载有关数据并访问更多的技术资料。

本书收录StephenM.Stigler的22篇论文，主要关于统计的发展历史，同时涉及统计思维、统计标准与统计检测等诸多方面。本书特别关注统计学史的两个方面。首要的方面包括了概念性的问题，这些问题出现在社会科学和自然科学领域对数据的解读上，非常艰深难懂。另一方面是数学方法问题，具有相当的技术复杂性，出现在对概率模型的建立和运用中。我们需要用这些模型来明确对不确定性的描述，否则无法判断结论及预测的可靠性。
全书共分为五个部分。第一部分讲述皮尔逊所受到的挑战，接着探讨凯特勒在1831年为赋予个体集合的平均值意义而做出的努力。第二部分主要介绍高尔顿的观点以及一些相关观点的进展。第三部分回顾的是更久远的17世纪，以及什么是数理概率在科学问题分析中的最早应用。第四部分关注的是“发现”在两个层面上的问题：“发现”作为科学社会学中的一个主旨，以及公众是如何看待一个新发现的。第五部分探讨的是统计对于标准的作用，以及标准在统计中的角色。

《帕尔格雷夫世界历史统计:欧洲卷1750-1993(第4版)》内容简介为：一、《帕尔格雷夫世界历史统计:欧洲卷1750-1993(第4版)》是三卷本《世界历史统计》的“欧洲卷”，覆盖了欧洲全部主要国家和政治体自1750年以来社会经济基本指标的可查连续统计数据。连同该书的“亚洲、非洲和大洋洲卷”以及“美洲卷”，《世界历史统计》是国际学术界第一本全面覆盖近代以来并延续至今的世界各地区和各主要国家及政治体的详尽统计数据汇编，可广泛用于经济研究、历史研究和国际研究等所有社会科学领域，毫无疑问将成为社会科学各学科的研究者和学习者必不可少的参考工具书。
二、《世界历史统计•欧洲卷》的全部统计指标分为十大类，它们是：
A 人口和生命统计
B 劳动力
C 农业
D 工业
E 对外贸易
F 交通通讯
G 财政金融
H 物价
I 教育
J 国民账户
在每一大类标题下细分各个具体的统计指标，例如：除了全国人口数之外还有国内地区人口数统计指标；工农业产量统计数据分别按基本产品划分；“财政金融”包括银行体系和政府税收；“国民账尸”除了有各国国内生产总值，还有各国各主要产业部门的比重以及对外收支数据等等。除了这些全书统一编排的统计数据之外，编著者还根据所掌握的最新统计发现和研究资料，针对若干国家或若干时期补充列出参考性数据，帮助读者进一步了解相关信息。

由统计学家Woods和语言学家Hughes，Fletcher合著的《语言研究中的统计方法》（Statistics in language studies）是剑桥语言学系列教材之一。这本书结合语言习得、语言变异和语言测试等方面的大量研究实例，介绍了统计分析的基本概念、方法和技术。读者可以把这些技术应用到自己的研究领域中去，也可以作为一种知识基础，评价和利用统计分析文献。

《应用随机过程概率模型导论》是一部经典的随机过程著作, 叙述深入浅出、涉及面广，主要内容有随机变量、条件概率及条件期望、离散及连续马尔可夫链、指数分布、泊松过程、布朗运动及平稳过程、更新理论及排队论等；也包括了随机过程在物理、生物、运筹、网络、遗传、经济、保险、金融及可靠性中的应用，特别是有关随机模拟的内容, 给随机系统运行的模拟计算提供了有力的工具。《应用随机过程概率模型导论》有约700道习题, 其中带星号的习题还提供了解答。

Unlike most other texts on the subject, this clear, concise introduction to the theory of microscopic bodies treats the modern theory of critical phenomena. Provides up-to-date coverage of recent major advances, including a self-contained description of thermodynamics and the classical kinetic theory of gases, interesting applications such as superfluids and the quantum Hall effect, several current research applications, The last three chapters are devoted to the Landau-Wilson approach to critical phenomena. Many new problems and illustrations have been added to this edition.

《实用多元统计分析(第6版)》多元统计分析是统计学中内容十分丰富、应用范围极为广泛的一个分支。在自然科学和社会科学的许多学科中，研究者都有可能需要分析处理有多个变量的数据的问题。能否从表面上看起来杂乱无章的数据中发现和提炼出规律性的结论，不仅需要对所研究的专业领域有很好的训练，而且要掌握必要的统计分析工具。对研究者来说，《实用多元统计分析》是学习掌握多元统计分析的各种模型和方法的一本有价值的参考书：首先，它做到了“浅入深出”，既可供初学者入门，又能使有较深基础的人受益；其次，它既侧重于应用，又兼顾必要的推理论证，使学习者既能学到“如何”做，又能在一定程度上了解“为什么”这样做；最后，它内涵丰富、全面，不仅基本包括各种在实际中常用的多元统计分析方法，而且对现代统计学的最新思想和进展有所介绍。

本书围绕对基因组学、蛋白质组学和生物信息学的概括描述，向读者介绍了近几年来生物学以及医学生物学研究方法上的发展，以及这些方法在研究思维上的深远影响。作者以通俗易懂的语言将这三个方面组成一个研究、探索问题的互动平台，使读者对生物信息学有一个系统的认识和了解，利于更深入的研究。内容主要包括基因组序列、基因组变异、基因组表达、DNA芯片、蛋白质组学、全基因组学以及基因组学在医学病例中的应用等，同时穿插问题探讨、数学备忘录等使内容更加丰富，并附有图片光盘利于读者参考。
本书可作生物学专业本科生、研究生的生物信息学教材或教学辅导书，亦可供分子生物学、生物化学、细胞生物学以及医学、药学等领域的科研人员参考。

本书主要包含国外反映近代数学发展的纯数学与应用数学方面的优秀书籍，天元基金邀请国内各个方向的知名数学家参与选题的工作，经专家遴选、推荐而出版。
目录
Preface
1 Preliminaries, notations and conventions
1.1 Elements of topology
1.2 Measure theory
1.3 Functions of bounded variation. Riemann-Stieltjes integral
1.4 Sequences of independent random variables
1.5 Convex functions. Holder and Minkowski inequalities
1.6 The Cauchy equation
2 Basic notions in functional analysis
2.1 Linear spaces
2.2 Banach spaces
2.3 The space of bounded linear operators
3 Conditional expectation
3.1 Projections in Hilbert spaces
3.2 Definition and existence of conditional expectation
3.3 Properties and examples
3.4 The Radon-Nikodym Theorem
3.5 Examples of discrete martingales
3.6 Convergence of self-adjoint operators
3.7 ... and of martingales
4 Brownian motion and l-Iilbert spaces
4.1 Gaussian families & the definition of Brownian motion
4.2 Complete orthonormal sequences in a Hilbert space
4.3 Construction and basic properties of Brownian motion
4.4 Stochastic integrals
5 Dual spaces and convergence of probability measures
5.1 The Hahn-Banach Theorem
5.2 Form of linear functionals in specific Banach spaces
5.3 Thedual of an operator
5.4 Weak and weak* topologies
5.5 The Central Limit Theorem
5.6 Weak convergence in metric spaces
5.7 Compactness everywhere
5.8 Notes on other modes of convergence
6 The Gelfand transform and its applications
6.1 Banach algebras
6.2 The Gelfand transform
6.3 Examples of Gelfand transform
6.4 Examples of explicit calculations of Gelfand transform
6.5 Dense subalgebras of C(S)
6.6 Inverting the abstract Fourier transform
6.7 The Factorization Theorem
7 Semigroups of operators and Levy processes
7.1 The Banach-Steinhaus Theorem
7.2 Calculus of Banach space valued functions
7.3 Closed operators
7.4 Semigroups of operators
7.5 Brownian motion and Poisson process semigroups
7.6 More convolution semigroups
7.7 The telegraph process semigroup
7.8 Convolution semigroups of measures on semigroups
8 Markov processes and semigroups of operators
8.1 Semigroups of operators related to Markov processes
8.2 The Hille-Yosida Theorem
8.3 Generators of stochastic processes
8.4 Approximation theorems
9 Appendixes
9.1 Bibliographical notes
9.2 Solutions and hints to exercises
9.3 Some commonly used notations
References
Index