《时间序列分析：预测与控制》内容始终都是时间序列领域的权威。第4版仍然分为5个部分，相对第3版新增内容主要有非线性和长记忆模型、多元时间序列分析以及前馈控制，其余各章节根据现实和教学需要均有不同程度的更新。在本书中，几位统计学大师用极其通俗的语言，结合大量的实例，阐明了时间序列分析的精髓。本书内容十分丰富，叙述简明，强调实际应用。相信每一位研读此书的读者都会获益匪浅。 本书可作为统计和相关专业高年级本科生或研究生教材，也可以作为统计专业技术人员的参考书。

If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data

《计量经济学导论(第3册)》从计量经济学专业人士的视角来讲授计量经济学导论，不仅使这门学科更有意思，而且实际上讲解起来还更简单。其内容有：计量经济学的性质与经济数据、简单回归模型等。

《应用回归分析(第3版)》写作的指导思想是在不失严谨的前提下，明显不同于纯数理类教材，努力突出实际案例的应用和统计思想的渗透，结合统计软件全面系统地介绍回归分析的实用方法，尽量结合中国社会经济、自然科学等领域的研究实例，把回归分析的方法与实际应用结合起来，注意定性分析与定量分析的紧密结合，努力把同行以及我们在实践中应用回归分析的经验和体会融入其中。 回归分析是统计学中一个非常重要的分支，在自然科学、管理科学和社会经济等领域有着非常广泛的应用。《应用回归分析(第3版)》是针对统计学专业和财经管理类专业教学的需要而编写的。

《MATLAB统计分析与应用:40个案例分析》从实际应用的角度出发，以大量的案例详细介绍了MATLAB环境下的统计分析与应用。《MATLAB统计分析与应用:40个案例分析》主要内容包括：利用MATLAB制作统计报告或报表；从文件中读取数据到MATLAB；从MATLAB中导出数据到文件；数据的平滑处理、标准化变换和极差归一化变换；生成一元和多元分布随机数；蒙特卡洛方法；参数估计与假设检验；Copula理论及应用实例；方差分析；基于回归分析的数据拟合；聚类分析；判别分析；主成分分析；因子分析；图像处理中的统计应用等。 《MATLAB统计分析与应用:40个案例分析》可以作为高等院校本科生、研究生的统计学相关课程的教材或教学参考书，也可作为从事数据分析与数据管理的研究人员的参考用书。

In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps you discover the nature of statistics and understand its essential role in scientific research.

《暨南大学研究生教材•多元统计分析及R语言建模》共分15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。《暨南大学研究生教材•多元统计分析及R语言建模》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。《暨南大学研究生教材•多元统计分析及R语言建模》还可作为非统计学专业研究生的量化分析教材。

《统计模拟(第4版)》首先介绍了产生某些分布随机数的一些方法， 之后又较详细地介绍了统计模拟中常用的一些方法， 如离散事件模拟方法、方差缩减技术、模拟数据的统计分析方法、统计验证方法、MCMC 方法等； 并通过某些实例， 对这些方法的应用进行了较详细的说明。《统计模拟(第4版)》最后还提供了不同难度的习题。统计模拟是数理统计中非常有用的工具之一， 它是利用计算机产生某概率模型的随机数，再通过这些随机数来模拟真实模型。 《统计模拟(第4版)》可作为高等院校数学、统计学、科学计算、保险学和精算学等专业的本科教材， 也可作为工程技术人员和精算师等应用工作者的参考用书。

《统计模型:理论和实践(英文版·第2版)》内容简介：Some books are correct. Some are clear. Some are useful. Some are entertaining. Few are even two of these. This book is all four. Statistical Models: Theory and Practice is lucid, candid and insightful, a joy to read. We are fortunate that David Freedman finished this new edition before his death in late 2008. We are deeply saddened by his passing, and we greatly admire the energy and cheer he brought to this volume——and many other projects——-during his final months.

This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.

《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。

Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collection Bayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

《统计推断原理(英文版)》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。 《统计推断原理(英文版)》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。

本书介绍的实用技巧运用了统计学原理，还借鉴了教育学和心理学上的测量和实验研究方法。这些技巧可以帮你解决商业、游戏以及日常生活中的各类问题。 本书主要内容： 在德州扑克、二十一点、轮盘赌、骰子游戏甚至买彩票时如何聪明地下注 设计能稳操胜券的酒吧赌注，赢到钱，在朋友面前赚足面子 预测体育比赛结果，知道足球比赛中何时应该“得两分” 揭秘惊人巧合，辨别真正的随机行为和表面上的随机行为 识别伪造数据，揭穿欺骗行为，破解密码 如何将观察结果与被观察对象分离 你是一位睡梦中都在做统计的统计迷，还是能够从趣味解题中找到乐趣的普通人？无论如何，只要善用本书介绍的知识，都能大大提高自己做事的成功几率。

Now updated with new research and even more intuitive explanations, a demystifying explanation of how managers can inform themselves to make less risky, more profitable business decisions This insightful and eloquent book will show you how to measure those things in your own business that, until now, you may have considered "immeasurable," including customer satisfaction, organizational flexibility, technology risk, and technology ROI. Adds even more intuitive explanations of powerful measurement methods and shows how they can be applied to areas such as risk management and customer satisfaction Continues to boldly assert that any perception of "immeasurability" is based on certain popular misconceptions about measurement and measurement methods Shows the common reasoning for calling something immeasurable, and sets out to correct those ideas Offers practical methods for measuring a variety of "intangibles" Adds recent research, especially in regards to methods that seem like measurement, but are in fact a kind of "placebo effect" for management - and explains how to tell effective methods from management mythology Written by recognized expert Douglas Hubbard-creator of Applied Information Economics-"How to Measure Anything, Second Edition" illustrates how the author has used his approach across various industries and how any problem, no matter how difficult, ill defined, or uncertain can lend itself to measurement using proven methods.

非参数统计是21世纪统计理论的三大发展方向之一。标准的参数方法强烈地依赖于对数据分布的假设，而非参数方法对模型要求甚少，且更加简单和稳健。随着计算工具的发展，非参数统计模型在许多领域中有越加广泛的应用。非参数统计不仅是统计类学科的必修课，也是统计应用工作者必须掌握的基本方法和思想。 　　本书是作者多年从事非参数统计研究和教学的经验总结。作者用清晰、简洁的语言和丰富的实例，为读者介绍了何时以及如何应用最普遍的非参数统计方法。书后配备了大量意义丰富的习题并附有部分答案。本书为国外众多学校所采用，是一本备受赞誉的非参数统计方面的权威教材。 　　非参数统计为有效地分析试验设计及其实际问题中所获得的数据提供了丰富而有说服力的统计工具，而本书则从问题背景与动机、方法引进、理论基础、计算机实现、应用实例、文献综述等诸多方面介绍了非参数统计方法，其内容包括：基于二项分布的检验、列联表、秩检验、Kolmogorov—Smirnov型统计量等，本书内容丰富、思路清晰、层次分明，在强调实用性的同时，突出了应用方法与理论的结合，书中的正文和习题中都提供了大量的实际案例，书中最后有许多统计用表以及奇数号习题解答和术语索引。 本书作为非参数统计的基础教材，适用于统计学专业的高年级本科生和研究生课程的教学，也可提供给从事统计学应用与研究、数据的分析处理及其相关领域的专业人员阅读与参考。

《统计学:在经济和管理中的应用》(第6版)作者三步走的问题解决方法论把统计问题的解答分解成可控的三个部分：识别、计算、解释。此外，读者还可以到相关网站免费下载CD资源，这一有益的工具为学习统计学提供了新的路径，其内容包括19个看图统计控件、Data Analysis Plus 4．0、Microsoft，Excel插件、学习向导以及以Excel、Minitab、JMP、SPSS与ASCⅡ等格式存储的数据文件。

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout. Author resource page: http://www.stat.columbia.edu/~gelman/arm/

《应用随机过程》是现代应用随机过程教材，内容从入门知识到学术前沿，包括预备知识、随机过程的基本类型、Poisson过程、更新过程、Markov链、鞅、Brown运动、随机积分、随机微分方程及其应用和Levy过程等，《应用随机过程》配有大量与社会、经济、金融、生物等专业相关的例题和