为什么有些酒吧这个礼拜人潮涌动，下个礼拜却空空荡荡？为什么《隐藏的逻辑》能在畅销榜单上久居不下？为什么邻居一夜之间成了暴发户？为什么股市会起伏波动？要找到这些问题的答案，就要像物理学家研究原子一样来研究人类社会，要思考的是模式，而不是人。多少年来，人类做决策的特性把大多数的经济学家和社会理论家都搞糊涂了，他们依赖一种老式的思维方式，认为人类社会之所以复杂是因为人是复杂的。现在，理论物理学家马克·布坎南（Mark Buchanan）告诉我们，在人类社会正在上演一场“量子革命”。物理学法则开始为我们描绘出一幅有关人或“社会原子”的崭新图像，而且与现实存在的个体自由意志毫不冲突。混乱的原子活动能够组合成精准的热力学，人类的自由个体也同样能组合成可预测的模式。社会物理学家能剖析潮流的变化；能预测企业是成是败：能解释犯罪增多的原因。布坎南在这本开阔眼界的书里提出，了解群体组织的规律是我们这个时代面临的主要挑战。《隐藏的逻辑》例证丰富，论点尖锐，容易理解，充满了智趣的游戏和刺激的实验，为我们看待人的社会行为提供了一个全新的视角。

Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including, matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.

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.

First Edition, Winner of the prestigious William James Award from the American Psychological Association An understanding of the principles of rational decision making can help students improve the quality of their lives. Intended as an introductory textbook, the material in Rational Choice in an Uncertain World is not only of scholarly interest, but practical as well. Created specifically for courses on judgement and decision-making, this book makes research readily accessible to both undergraduate and graduate students. This Second Edition of the award-winning book, Rational Choice in an Uncertain World (1988) by Robyn M. Dawes, is sure to interest and enlighten students at all levels. This new edition features: * New student friendly chapter introductions as well as conclusions and cross-references between chapters. * Award-winning authors are respected professors with over 30 years of experience in the field. * Practical, everyday examples from such areas as finance, medicine, law, and engineering.* Comprehensive and up-to-date information keep this edition abreast of the changing ideas within the discipline * Additional discussion of the descriptive, psychological models of decision making to expand upon the original emphasis on normative, rational, 'Expected Utility Theory' models. Equipped with this knowledge and an understanding of the principles of rational decision making, both undergraduate and graduate students can help improve the quality of their choices and, thus, their life.

Eighty years ago, Ettore Majorana, a brilliant student of Enrico Fermi, disappeared under mysterious circumstances while going by ship from Palermo to Naples. How is it possible that the most talented physicist of his generation vanished without leaving a trace? It has long been speculated that Majorana decided to abandon physics, disappearing because he had precociously realized that nuclear fission would inevitably lead to the atomic bomb. This book advances a different hypothesis. Through a careful analysis of Majorana's article "The Value of Statistical Laws in Physics and Social Sciences," which shows how in quantum physics reality is dissolved into probability, and in dialogue with Simone Weil's considerations on the topic, Giorgio Agamben suggests that, by disappearing into thin air, Majorana turned his very person into an exemplary cipher of the status of the real in our probabilistic universe. In so doing, the physicist posed a question to science that is still awaiting an answer: What is Real?

这是一本具有李政道特色的统计力学专著。它凝聚了李先生在统计力学方面的治学结晶，自成体系。虽只有短短的四章，却几乎概括了统计力学的所有精髓。读者可以使用本书作为学习统计力学的入门教材，也可以在使用别的教材时用它作为学习的参考和补充材料。李政道先生治学严谨，一切推导都从最基本假定出发的研究风格，在本书中得到充分的体现。

这是一本专门讲述伽罗瓦理论的教材。内容包括伽罗瓦理论基本定理和多项式方程的根式可解性、伽罗瓦群的计算及其反问题，《伽罗瓦理论：天才的激情》强调通过伽罗瓦对应，可将代数数域中的问题转化成群论的问题加以解决。作为这种思想的应用，证明了代数基本定理，解决了e和的超越性及尺规作图的四大古代难题。为方便读者查阅，附录中详细梳理了所要用到的群、环、域方面的结论。每节配有充足的习题并包含提示。
《伽罗瓦理论：天才的激情》可作为高等学校数学类各专业的教材，也可供其他相关专业参考。

Designed for researchers and graduate students in machine learning, this book introduces the theory of variational Bayesian learning, a popular machine learning method, and suggests how to make use of it in practice. Detailed derivations allow readers to follow along without prior knowledge of the specific mathematical techniques.

David A. Freedman presents here a definitive synthesis of his approach to causal inference in the social sciences. He explores the foundations and limitations of statistical modeling, illustrating basic arguments with examples from political science, public policy, law, and epidemiology. Freedman maintains that many new technical approaches to statistical modeling constitute not progress, but regress. Instead, he advocates a 'shoe leather' methodology, which exploits natural variation to mitigate confounding and relies on intimate knowledge of the subject matter to develop meticulous research designs and eliminate rival explanations. When Freedman first enunciated this position, he was met with scepticism, in part because it was hard to believe that a mathematical statistician of his stature would favor 'low-tech' approaches. But the tide is turning. Many social scientists now agree that statistical technique cannot substitute for good research design and subject matter knowledge. This book offers an integrated presentation of Freedman's views.

This is the second edition of a coherent introduction to the subject of asymptotic statistics as it has developed over the past 50 years. It differs from the first edition in that it is now more 'reader friendly' and also includes a new chapter on Gaussian and Poisson experiments, reflecting their growing role in the field. Most of the subsequent chapters have been entirely rewritten and the nonparametrics of Chapter 7 have been amplified. The volume is not intended to replace monographs on specialized subjects, but will help to place them in a coherent perspective. It thus represents a link between traditional material - such as maximum likelihood, and Wald's Theory of Statistical Decision Functions -- together with comparison and distances for experiments. Much of the material has been taught in a second year graduate course at Berkeley for 30 years.

'This book covers the dominant theoretical approaches to the approximate solution of hard combinatorial optimization and enumeration problems. It contains elegant combinatorial theory, useful and interesting algorithms, and deep results about the intrinsic complexity of combinatorial problems. Its clarity of exposition and excellent selection of exercises will make it accessible and appealing to all those with a taste for mathematics and algorithms' - Richard Karp, University Professor, University of California at Berkeley. Following the development of basic combinatorial optimization techniques in the 1960s and 1970s, a main open question was to develop a theory of approximation algorithms. In the 1990s, parallel developments in techniques for designing approximation algorithms as well as methods for proving hardness of approximation results have led to a beautiful theory. The need to solve truly large instances of computationally hard problems, such as those arising from the Internet or the human genome project, has also increased interest in this theory. The field is currently very active, with the toolbox of approximation algorithm design techniques getting always richer. It is a pleasure to recommend Vijay Vazirani's well-written and comprehensive book on this important and timely topic. "I am sure the reader will find it most useful both as an introduction to approximability as well as a reference to the many aspects of approximation algorithms' - Laszlo Lovasz, Senior Researcher, Microsoft Research.

A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation presents a complete treatment of the subject, organizing and clarifying the diverse types of biases into a conceptual framework. The book treats various sources of bias in comparative studies—both randomized and observational—and offers guidance on how they should be addressed by researchers. Utilizing a relatively simple mathematical approach, the author develops a theory of bias that outlines the essential nature of the problem and identifies the various sources of bias that are encountered in modern research. The book begins with an introduction to the study of causal inference and the related concepts and terminology. Next, an overview is provided of the methodological issues at the core of the difficulties posed by bias. Subsequent chapters explain the concepts of selection bias, confounding, intermediate causal factors, and information bias along with the distortion of a causal effect that can result when the exposure and/or the outcome is measured with error. The book concludes with a new classification of twenty general sources of bias and practical advice on how mathematical modeling and expert judgment can be combined to achieve the most credible causal conclusions. Throughout the book, examples from the fields of medicine, public policy, and education are incorporated into the presentation of various topics. In addition, six detailed case studies illustrate concrete examples of the significance of biases in everyday research. Requiring only a basic understanding of statistics and probability theory, Bias and Causation is an excellent supplement for courses on research methods and applied statistics at the upper-undergraduate and graduate level. It is also a valuable reference for practicing researchers and methodologists in various fields of study who work with statistical data. This book is the winner of the 2010 PROSE Award for Mathematics from The American Publishers Awards for Professional and Scholarly Excellence

《统计物理学2:凝聚态理论(第4版)》是一部享誉世界的理论物理学巨著，是反映经典物理学向现代物理学转变的里程碑式的重要著作，于1962年获得列宁奖。原著为俄文，现已有十余种文字的分卷译本，六种文字的全卷译本。本教程中的七卷是由诺贝尔物理学奖获得者、苏联科学院院士、伟大的理论物理学家朗道和他的学生、苏联科学院院士、杰出的理论物理学家E.M.栗弗席兹在20世纪40—50年代陆续编写而成的，另外三卷由栗弗席兹和俄罗斯科学院院士皮塔耶夫斯基等人按朗道的计划在20世纪60—70年代编写完成，后经不断补充完善，现已成为举世公认的经典学术著作。本套教程内容丰富、立论明确、论证严谨、物理图像清晰，涵盖了理论物理学从微观到宏观的各个领域，各卷中附有丰富的习题及解答，是学习理论物理学的必备参考书。

计量史学研究入门，ISBN：9787301215029，作者：霍俊江 著

《统计物理学中的量子场论方法(第3版)》原书为1962年的俄文第1版，是这个领域内的世界上第一本专著和教材，也是早期凝聚态理论中最经典和最权威的著作之一，同时也是中国在20世纪的60—70年代学习凝聚态理论（早期场论方法）的最早和最普及的一本专著和教材。
根据原书1962年的俄文第1版，1963年美国和中国均出版了相应的英译本和中译本（中文译者：郝柏林）。此后，在1965年欧美国家又在原书1962年的俄文第1版和原作者提供的补充和订正材料的基础上，翻译出版了该书第2版的英译本。
中国的郝柏林院士参考了该书以往的几个版本，对其进行重新翻译出版，且将原作者为英译本准备的补充和订正也加了进去。

It is widely held that Bayesian decision theory is the final word on how a rational person should make decisions. However, Leonard Savage--the inventor of Bayesian decision theory--argued that it would be ridiculous to use his theory outside the kind of small world in which it is always possible to "look before you leap." If taken seriously, this view makes Bayesian decision theory inappropriate for the large worlds of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian decision theory--and when does it need to be modified? Using a minimum of mathematics, Rational Decisions clearly explains the foundations of Bayesian decision theory and shows why Savage restricted the theory's application to small worlds.
The book is a wide-ranging exploration of standard theories of choice and belief under risk and uncertainty. Ken Binmore discusses the various philosophical attitudes related to the nature of probability and offers resolutions to paradoxes believed to hinder further progress. In arguing that the Bayesian approach to knowledge is inadequate in a large world, Binmore proposes an extension to Bayesian decision theory--allowing the idea of a mixed strategy in game theory to be expanded to a larger set of what Binmore refers to as "muddled" strategies.
Written by one of the world's leading game theorists, Rational Decisions is the touchstone for anyone needing a concise, accessible, and expert view on Bayesian decision making.

Brian Skyrms constructs a theory of "dynamic deliberation" and uses it to investigate rational decisionmaking in cases of strategic interaction. This illuminating book will be of great interest to all those in many disciplines who use decision theory and game theory to study human behavior and thought. Skyrms begins by discussing the Bayesian theory of individual rational decision and the classical theory of games, which at first glance seem antithetical in the criteria used for determining action. In his effort to show how methods for dealing with information feedback can be productively combined, the author skillfully leads us through the mazes of equilibrium selection, the Nash equilibria for normal and extensive forms, structural stability, causal decision theory, dynamic probability, the revision of beliefs, and, finally, good habits for decision. The author provides many clarifying illustrations and a handy appendix called "Deliberational Dynamics on Your Personal Computer." His powerful model has important implications for understanding the rational origins of convention and the social contract, the logic of nuclear deterrence, the theory of good habits, and the varied strategies of political and economic behavior.

This comprehensive discussion of the problem of rational belief develops the subject on the pattern of Bayesian decision theory. The analogy with decision theory introduces philosophical issues not usually encountered in logical studies and suggests some promising new approaches to old problems.

A problem-oriented text for evaluating statistical procedures through decision and game theory. First-year graduates in statistics, computer experts and others will find this highly respected work best introduction to growing field.

R.A. Fisher has had more influence on the development of statistical theory and practice than any other twentieth-century statistician. His writings (both in paper and book form) have proved to be as relevant to present-day statisticians as they were when first published. This book brings together as a single volume three of Fisher's most influential textbooks: Statistical Methods for Research Workers, The Design of Experiments , and Statistical Methods and Scientific Inference . In this new edition Frank Yates has provided a foreword which sheds fresh light on Fisher's thinking and on the writing and reception of each of the books. He discusses some of the key issues tackled in the three books and reflects on how the ideas expressed have come to permeate modern statistical practice.