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Jingdong book

深入浅出数据分析

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Jingdong book

深入浅出数据分析

Name: 深入浅出数据分析
Brand: Jingdong book
SKU: 3118173071
Price: 37.65 USD
Availability: OutOfStock

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Editer Recommend

我们生活在数据的天地里，你的工作就是淋漓尽致地发挥数据的作用。从哪里起步？米尔顿编著的《深入浅出数据分析》将为你提供帮助：利用Excel或0penoffice应用程序组织数据，在R应用程序中进行进一步整理，通过散点图和直方图找出有意义的模式，借助启发式算法做出结论，通过实验和假定测试预见未来，再以清楚直观的图形展示分析结果。无论你是研究新产品可行性的开发人员，还是评估广告效果的市场营销经理；无论你是向客户呈报数据的营销员，还是管理所有这些数据密集型部门及种种其他事务的个人企业家，《深入浅出数据分析》都能为你带来全面的学习体验，让你将数据转变为事业中有用的工具。

Content Description

《深入浅出数据分析》以类似“章回小说”的活泼形式，生动地向读者展现出色的数据分析人员应知应会的技术：数据分析基本步骤、实验方法、优化方法、假设检验方法、贝叶斯统计方法、主观概率法、启发法、直方图法、回归法、误差处理、相关数据库、数据整理技巧；正文之后，意犹未尽地以三篇附录介绍数据分析十大要务、R工具及ToolPak工具，在充分展现目标知识以外，为读者搭建了走向深入研究的桥梁。

Author Description

Michael Milton,将自己的大半职业生涯献给了非盈利机构，帮助这些机构解析和处理，从赞助人那里收集来的数据，提高融资能力。Michael Milton拥有新佛罗里达学院哲学学位及耶鲁大学宗教伦理学学位。多年来，他博览群书，这些书籍虽字字珠玑，却枯燥乏味；蓦然抬首，深入浅出（HeadFirst）系列图书让他眼前一亮，他欣然抓住机会，写出了这本同样字字珠玑，兼振奋人心的书。走出图书馆和书店，人们会看到他在跑步、摄影，以及亲手酿制啤酒。

Catalogue

1 数据分析引言：分解数据
2 实验：检验你的理论
3 最优化：寻找最大值
4 数据图形化：图形让你更精明
5 假设检验：假设并非如此
6 贝叶斯统计：穿越第一关
7 主观概率：信念数字化
8 启发法：凭人类的天性作分析
9 直方图：数字的形状
10 回归：预测
11 误差：合理误差
12 相关数据库：你能关联吗？
13 整理数据：井然有序
附录A 尾声：正文未及的十大要诀
附录B 安装R：启动R！
附录C 安装Excel分析工具：ToolPak

Book Abstract

吉姆：我们应该把这些数字忘掉，尽量多争取。数字不会让我们知道别人认为我们配得多少工资。老板心里有一个数字范围，我们要想办法争取上限值。
乔：我同意大部分数字都对我们没用，不会让我们知道别人认为我们配得多少工资。我也不知道该怎么摸清这一点。数字会让我们知道平均值，要求平均水平准没错。
吉姆：平均水平？你准是在开玩笑，干嘛想着中等？目标定高点！
弗兰克：我想应该更细致地分析分析，我们的信息很充分，谁知道这些数据会告诉我们什么呢？
乔：我们必须保险点，要随大流。中等水平很保险，只要求出加薪列的平均值，然后要求加这么多就行了。
吉姆：真是缩头乌龟！
弗兰克：看，数据表明职员是否提出过加薪、加薪年份、职员性别。这些数据对我们很有用，我们只要把数据调整成合适的格式就行。
吉姆：好吧，高手，说来听听。
弗兰克：没问题。首先，我们得想办法把这些数字整理成更有意义的……

Introduction

译者序
2010年2月，春节将至，我向博文视点的某个邮箱寄出了一封请求参加翻译任何一本图书的邮件。很快，有人回信了，内容简单明了：请下载并试译第1章1~17页内容。落款是博文视点编辑徐定翔。于是我试译，寄出，然后等待。春节过去了，一切都从节日的慵懒中苏醒过来——包括我的试译结果——它来了：通过。合作事项很快商定，工作就这样开始了。
如今已是2010年8月，稿件已如期交付，按照出版惯例，我可以占用一点篇幅，谈谈这本书。
正如O’Reilly出版社的HeadFirst系列的其他图书那样，本书在语言组织、排版设计方面非常有特色，用“新颖”二字形容毫不为过，用“周到”二字形容也十分妥当。
其构思跌宕起伏，其行文妙趣横生，无论读者是职场老手，还是业界新人；无论是字斟句酌，还是信手翻阅，相信都能跟着文字在职场中走上几回，体味数据分析领域的乐趣与挑战。一本技术图书，在传道授业之外，又为读者送上了章回小说的精彩。
这些设计巧妙的“章回”生动地向读者展现了数据分析基本步骤、实验方法、最优化方法、假设检验方法、贝叶斯统计方法、主观概率法、启发法、直方图法、回归法、误差处理、相关数据库、数据整理技巧，此后意犹未尽，又以3篇附录介绍数据分析十大要务、R工具及ToolPak工具，在尽情展现目标知识以外，为读者搭建了走向深入研究的桥梁。
与我们司空见惯的很多书籍不一样，本书更愿意引导读者进行思考，而不愿向读者灌输现成的条条框框去禁锢读者的想象空间。在本书点到即止的启发下，读者很有可能跃跃欲试，急不可待地要把目光投向更宽、更深的知识领域，发掘更多的数据分析知识，以便早日成为数据分析达人。
文章字里行间流露出作者传道授业的热忱，以下仅举两例：一是设法克服术语的障碍。这一点，英语使用者恐怕比中文使用者体会更深，层出不穷的英语术语甚至让以英语为母语的读者感到厌倦和头痛，作者深知这一点，于是尽量用浅显的语言表述，解除英语读者的心头之患；至于中文，感谢祖国语言的优秀特性，倘若作为译者的我没有在这里帮倒忙，术语方面的问题甚至可以忽略不计了。
二是设法实现理论与实践的转化。理论如何向实践转化，一向是学习者的难题。然而本书精心构思的“章回”体裁，却让理论知识与实际操作水乳交融，职场气息扑面而来，除了谈分析，作者也谈经济、谈局势、谈心理、谈做人，涉猎广泛，面面俱到。
能够理解，作者希望这本书成为读者书架上的常备手册，在读者走进数据分析领域之初，或是遇到从业疑难时，提供力所能及的帮助。我也如此希望。
最后，请容我借本序致谢：
感谢博文视点。
感谢徐定翔编辑对我的信任和指教。
感谢家人对我的理解和支持。
李芳
2010年8月

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