《R语言与统计分析》以数据的常用统计分析方法为基础，在简明扼要地阐述统计学基本概念、基本思想与基本方法的基础上，讲述与之相对应的R函数的实现，并通过具体的例子说明统计问题求解的过程。《R语言与统计分析》注重统计的思想性、方法的实用性和计算的可操作性。在内容的安排上不仅包含了基础统计分析中的探索性数据分析、参数估计与假设检验，还包括了非参数统计分析的常用方法、多元统计分析方法及贝叶斯统计分析方法。每一部分都通过具体例子重点讲述解决问题的思想、方法和在R中的实现过程。

【名人推荐】 “科学计算和数据分析社区已经等待这本书很多年了：大量具体的实践建议，以及大量综合应用方法。本书在未来几年里肯定会成为Python领域中技术计算的权威指南。” ——Fernando Pérez　加州大学伯克利分校 研究科学家， IPython的创始人之一 【内容简介】 还在苦苦寻觅用Python控制、处理、整理、分析结构化数据的完整课程？本书含有大量的实践案例，你将学会如何利用各种Python库（包括NumPy、pandas、matplotlib以及IPython等）高效地解决各式各样的数据分析问题。 由于作者Wes McKinney是pandas库的主要作者，所以本书也可以作为利用Python实现数据密集型应用的科学计算实践指南。本书适合刚刚接触Python的分析人员以及刚刚接触科学计算的Python程序员。 •将IPython这个交互式Shell作为你的首要开发环境。 •学习NumPy（Numerical Python）的基础和高级知识。 •从pandas库的数据分析工具开始。 •利用高性能工具对数据进行加载、清理、转换、合并以及重塑。 •利用matplotlib创建散点图以及静态或交互式的可视化结果。 •利用pandas的groupby功能对数据集进行切片、切块和汇总操作。 •处理各种各样的时间序列数据。 •通过详细的案例学习如何解决Web分析、社会科学、金融学以及经•济学等领域的问题。

Matlab is the accepted standard for scientific computing, used globally in virtually all Neuroscience and Cognitive Psychology laboratories. For instance, SPM, the most used software for the analysis and manipulation of fMRI images in research and clinical practice is fully programmed in matlab, and its use of the possibility to allow for sophisticated software modules to be freely added to the software has established it as the by far dominant software in the field. Many universities now offer, or are beginning to offer matlab introductory courses in their neuroscience and psychology programs. Nevertheless, so far there hasn't been a textbook specific to this market, and the use of the plethora of existing engineering focused Matlab textbooks is notoriously difficult for teaching the package in those environments. This is the first comprehensive teaching resource and textbook for the teaching of Matlab in the Neurosciences and in Psychology. Matlab is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environment. The idea is to empower advanced undergraduates and beginning graduate students by allowing them to design and implement their own analytical tools. As students advance in their research careers, they will have achieved the fluency required to understand and adapt more specialized tools as opposed to treating them as "black boxes". Virtually all computational approaches in the book are covered by using genuine experimental data that are either collected as part of the lab project or were collected in the labs of the authors, providing the casual student with the look and feel of real data. In some rare cases, published data from classical papers are used to illustrate important concepts, giving students a computational understanding of critically important research. The ability to effectively use computers in research is necessary in an academic environment that is increasingly focused on quantitative issues. Matlab represents an ideal language of scientific computing. It is based on powerful linear algebra structures which lend themselves to empirical problems on the one hand, while at the same time allowing the student to make rapid problem-oriented progress (particularly in terms of visualization of data points) without having to lose focus by worrying too much about memory allocation and other "plumbing" minutiae as would be required in other, more low-level programming languages such as C or C++. Currently, there are several books that provide introductions to Matlab that are either too generic and fundamental or too irrelevant for neuroscientists and cognitive psychologists who typically face a very circumscribed range of problems in data collection, data analysis and signal processing. Some non-book tutorials and primers that are in use in the community are typically out of date. Matlab versions are usually not backwards compatible. Many commands and functions used in older tutorials and primers, such as "flops" won't work in current versions of Matlab, necessitating a book that is timely and up-to-date. The complete lack of a relevant resource in this area, combined with a clearly felt need for such a text provided the primary and initial impetus for this project. The authors provide such a dearly needed resource adapting and pooling materials that developed for and used in highly rated courses involving the use of Matlab in Neuroscience at the University of Chicago. Two co-authors (PW and NH) have presented their respective work on teaching Matlab at national meetings and two of the co-authors (PW and MB) were awarded the coveted University of Chicago's Booth Prize for excellence in teaching these courses. (http://chronicle.uchicago.edu/070524/boothprize.shtml ). * The first comprehensive textbook on Matlab with a focus for its application in Neuroscience * Problem based educational approach with many examples from neuroscience and cognitive psychology using real data * Authors are award winning educators with strong teaching experience * Instructor's Website with figurebank, additional problems and examples, solutions, etc

《C++语言的设计与演化》是C++的设计者关于C++语言的最主要著作之一。作者综合性地论述了C++的发展历史，C++中各种重要机制的本质意义和设计背景，这些机制的基本用途和使用方法，讨论了C++所适合的应用领域及其未来的发展前景。全书共18章，分两大部分，其中第1部分（第1～9章）分别介绍了C++的史前时代、C with Classes、C++的诞生、C++语言设计规则、1985—1993年表、标准化、关注和使用、库、展望；第2部分（第10～18章）分别介绍了存储管理、重载、多重继承、类概念的精练、强制转换、模板、异常处理、名称空间、C语言预处理器。为便于查找与学习，全书最后附有专业术语索引。《C++语言的设计与演化》在帮助人们理解C++语言方面的作用是不可替代的。 书面向每个学习和关注C++语言的专业工作者、科研人员、教师及学生。

“本书语言流畅细腻，读起来如沐春风。它犹如一部波澜壮阔的计算机史诗，讲述了软件革命的恢弘历史，以及中流砥柱们的光辉事迹。故事并不是断断续续的，因为作者采用了微型传记的形式……他把历史写成了优美的散文，生动迷人又严谨有度。” ——David Gelernter，《纽约时报》 “这是一本给人启迪的著作，完美地展现了想象力的巨大力量。如果你想象得到，并把它编成代码，那么一定能够改变世界！” ——Boston Sunday Globe “本书把难懂的技术概念讲解得通俗易懂。对于那些对计算机内在结构好奇的人，这是一本能让其豁然开朗的好书。计算机科学界的前辈John McCarthy曾向作者抱怨过新闻记者的无知，本书就是作者对此作出的回应……与计算机行业相关的所有新闻记者都应该读一读这本书。” ——《纽约时报书评》 “这不是一本通常意义上的书，而是一部史诗。它讲述的不是技术，而是那些设计编程语言和计算机软件的名人的故事……本书内容清晰易懂，简明扼要。软件工程让程序员不需要材料和工具也能有所创造，他们为此兴奋不已。他们能够凭空创造新的事物，唯一的限制就是自己的想象力。” ——《国际先驱论坛报》 “如果本书作者是一名程序员，那么他写的代码一定清晰有序，不需要复杂的结构或者奇怪的快捷方式就能跳转到正确的子程序上；他的写作风格也是如此。本书化繁为简，让读者与数学专家、桥牌高手、象棋大师、特立独行的科学家、批判传统观念的人，以及掀起软件革命的程序员们进行了一次愉悦的会面。” ——《新闻周刊》 “本书展现了技术缔造者们面对的挑战，是本旷世杰作。” ——《自然》周刊 聆听软件行业发展的精彩故事 领悟软件巨擘的深邃思想 放飞想象力，通过编码改变世界 Steve Lohr（作者）《纽约时报》高级作家和技术通讯记者，U .S. v. Microsoft一书合著者，现居住于纽约。 张沛玄（译者）1992年毕业于北京理工大学飞行器工程系固体火箭发动机专业，获得工学学士学位。2001年重回母校管理与经济学院就读，2004年毕业并获工商管理硕士学位。早年他曾从事软件开发，担任IT公司高级管理工作多年。

《穿越计算机的迷雾》从最基本的电学知识开始，带领读者一步一步、从无到有地制造一台能全自动工作的计算机。在这个过程中，读者可以学习到大量有趣的电学、数学和逻辑学知识，了解到它们是如何为电子计算机的产生创造条件，并促使它不断向着更快、更小、更强的方向发展。通过阅读《穿越计算机的迷雾》，读者可以很容易地理解自动计算实际上是如何发生的，而现代的计算机又是怎么工作的。以此为基础，在《穿越计算机的迷雾》的后面集中介绍了现代计算机的组成和主要功能，以及计算机核心与外部设备的接口，并对以操作系统为核心的软件进行了介绍。未经许可，不得以任何方式复制或抄袭《穿越计算机的迷雾》之部分或全部内容。