书名：Everybody Lies人人都在说谎：赤裸裸的数据真相
作者：Seth Stephens-Davidowitz
出版社名称：Bloomsbury Publishing
出版时间：2018
语种：英文
ISBN：9781408894736
商品尺寸：19.6 x 3.2 x 12.8 cm
包装：平装
页数：352（以实物为准）
★提供理解数据的全新角度
为什么很多数据公司的调研结果失真？怎样才能获得真正有效的数据样本？大众获取数据的有效途径是什么？作者赛思·斯蒂芬斯-达维多维茨在谷歌实验室潜心研究数据数年，他发现数据样本里很多内容都是无效的，所以得出的结论往往谬以千里。究其原因，人们太善于撒谎了，或者说人们无时无刻不在说谎。在本书Everybody Lies《人人都在说谎：赤裸裸的数据真相》中，他通过对有效数据的分析，得出了很多令人震惊的结论。同时，这本书为大众读者使用数据、分析数据提供了全新的方法和思考角度。

★用丰富的案例解读数据本质，了解世界到底是如何运作的
美国大选中获胜者意想不到的支持从何而来？对金融公司很重要的数据之一居然是月失业率？头一次约会哪些词汇可以暴露心里所想……在这本书中你可以读到各种各样的有趣数据案例，通过这些案例你会真正了解一个社会的真实面貌，不得不说，这是一本难能可贵的用科学的数据分析方法帮助我们更深入了解社会的书。赛思的分析方式颠覆了传统心理学和社会学研究。通过本书，你可以不断拓展自己的知识边界，用大数据思维客观分析身边发生的一切。

★升级版《魔鬼经济学》、《点石成金》
作者深受《魔鬼经济学》影响，不同的是，他是通过研究海量数据来了解世界是如何运作的。国外媒体盛赞：这本书结合了纳特·西尔弗《信号与噪声》的严谨分析，马尔科姆·格拉德威尔《异类》的故事性，和史蒂芬·列维特《魔鬼经济学》的幽默。

本书以一个引人入胜、充满启迪和智慧的视角，巧妙洞察我们现在可获得的大量信息，为我们提供了实用的数据分析方法，同时也揭示了深深埋藏在数据背后世界本来的样貌。对于想要通过数据了解和分析人类行为与社会的人而言，这本书精彩不容错过！

媒体评论：
“这是一次以搜索数据为导向的有关现代人类心理的旋风式旅程。这本书里的实证研究结果太有趣了，很多有趣的案例，让人欲罢不能！”——《经济学人》

“一种研究思想的全新方法，一个窥视人类内心从未有过的入口，斯蒂芬斯·达维多维茨的发现一次又一次颠覆我对自己国家和人民的认知，这本书魅力无限！”——斯蒂芬·平克《人性中的善良天使》作者

THE NEW YORK TIMES BESTSELLER
AN ECONOMIST BOOK OF THE YEAR
A NEW STATESMAN BOOK OF THE YEAR
Everybody lies, to friends, lovers, doctors, pollsters - and to themselves. In Internet searches, however, people confess the truth.
Insightful, funny and always surprising, Everybody Lies explores how this huge collection of data, unprecedented in human history, could just be the most important ever collected. It offers astonishing insights into the human psyche, revealing the biases deeply embedded within us, the questions we're afraid to ask that might be essential to our well-being, and the information we can use to change our culture for the better.

Review
“Time and again my preconceptions about my country and my species were turned upside-down by Stephens-Davidowitz's discoveries”(Steven Pinker, author of The Better Angels of Our Nature)

“Absorbing and impassioned... as an introduction to our fascinating new universe of data, Everybody Lies is hard to beat” (Financial Times)

“Everybody Lies is an astoundingly clever and mischievous exploration of what big data tells us about everyday life. Seth Stephens-Davidowitz is as good a data storyteller as I have ever met” (Steven Levitt, co-author, Freakonomics)

“A whirlwind tour of the modern human psyche. The empirical findings in Everybody Lies are so intriguing that the book would be a page-turner even if it were structured as a mere laundry list” (Economist)
有多少人买了书真正看完了？
你朋友的酒量有他说的那么大吗？
父母是否暗自喜欢男孩儿多于女孩儿？
电影里暴力镜头增多会导致犯罪率升高吗？
种族歧视在现如今的美国还严重吗？
特朗普的胜利有征兆吗，什么促成他赢得了大选？
……

你知道问题的答案吗，直觉会怎样告诉你？
作者赛思·斯蒂芬斯-达维多维茨是一位前谷歌数据科学家和专栏作家。他的研究发现，世界充满了谎言，人类或出于善意或出于恶意，无时无刻不在说谎。对于以上以及类似的很多问题，传统的统计调研方法得出的结论很多是错误的，误导了我们的认知。

但是，人们往往在一个地方放下戒备、吐露心声，那就是互联网。每一次搜索、每一次点击、每一次停留、每一次关闭……在线生成了大量的数据，暴露着你的真实想法、欲望、恐惧和职业，而海量的数据形成的真实而庞大的数据宝库会总结出意想不到的结论和趋势。

在这本应时的力作Everybody Lies《人人都在说谎：赤裸裸的数据真相》中，作者从一个个备受关注的话题切入，用他独特的数据分析方法得出了很多颠覆认知的结论。很多问题的答案正暗藏于看似没有关联的因素中，很多直觉和经验给出的答案与事实相差千里，大数据被合理使用其实比数据库的大更重要……作者广博的知识面将从多个层面拓展我们的认知边界；书中生动有趣的描写让你不想错过任何一个细节。
赛思·斯蒂芬斯-达维多维茨，《纽约时报》专栏作者，沃顿商学院客座讲师，前谷歌数据科学家。他在斯坦福大学获得哲学学士学位，并以美国大学优等生的身份毕业，之后获得哈佛大学经济学博士学位。他用新的大数据源揭示了不为人知的行为和态度，这一研究发现登上了《公共经济学》杂志和其他著名刊物，现居纽约市。

Seth Stephens-Davidowitzis a New York Times op-ed contributor, a visiting lecturer at The Wharton School, and a former Google data scientist. He received a BA in philosophy from Stanford, where he graduated Phi Beta Kappa, and a PhD in economics from Harvard. His research - which uses new, big data sources to uncover hidden behaviours and attitudes - has appeared in the Journal of Public Economics and other prestigious publications. He lives in New York City.
If you' re thirty-three years old and have attended a few Thanksgivings in a row without a date, the topic of mate choice is likely to arise. And just about everybody will have an opinion.
"Seth needs a crazy girl, like him," my sister says.
"You' re crazy! He needs a normal girl, to balance him out," my brother says.
"Seth's not crazy," my mother says.
"You' re crazy! Of course, Seth is crazy," my father says.
All of a sudden, my shy, soft-spoken grandmother, quiet through the dinner, speaks. The loud, aggressive New York voices go silent, and all eyes focus on the small old lady with short yellow hair and still a trace of an Eastern European accent."Seth, you need a nice girl. Not too pretty. Very smart. Good with people. Social, so you will do things. Sense of humor, because you have a good sense of humor."
Why does this old woman's advice command such attention and respect in my family? Well, my eighty-eight-year-old grandmother has seen more than everybody else at the table. She's observed more marriages, many that worked and many that didn't. And over the decades, she has cataloged the qualities that make for successful relationships.
At that Thanksgiving table, for that question, my grandmother has access to the largest number of data points. My grandmother is Big Data.
In this book, I want to demystify data science. Like it or not, data is playing an increasingly important role in all of our lives-and its role is going to get larger. Newspapers now have full sections devoted to data. Companies have teams with the exclusive task of analyzing their data. Investors give start-ups tens of millions of dollars if they can store more data. Even if you never learn how to run a regression or calculate a confidence interval, you are going to encounter a lot of data-in the pages you read, the business meetings you attend, the gossip you hear next to the watercoolers you drink from.
Many people are anxious over this development. They are intimidated by data, easily lost and confused in a world of numbers. They think that a quantitative understanding of the world is for a select few left-brained prodigies, not for them.
As soon as they encounter numbers, they are ready to turn the page, end the meeting, or change the conversation.