An audacious, irreverent investigation of human behavior—and a first look at a revolution in the making
Our personal data has been used to spy on us, hire and fire us, and sell us stuff we don’t need. In Dataclysm, Christian Rudder uses it to show us who we truly are.
For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.
In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.
Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.
From the Hardcover edition.
Features of the Fourth Edition include:New material on sample size calculations for chance-corrected agreement coefficients, as well as for intraclass correlation coefficients. The researcher will be able to determine the optimal number raters, subjects, and trials per subject.The chapter entitled “Benchmarking Inter-Rater Reliability Coefficients” has been entirely rewritten.The introductory chapter has been substantially expanded to explore possible definitions of the notion of inter-rater reliability.All chapters have been revised to a large extent to improve their readability.
Accompanying the book is the Exploratory Software for Confidence Intervals (ESCI) package, free software that runs under Excel and is accessible at www.thenewstatistics.com. The book’s exercises use ESCI's simulations, which are highly visual and interactive, to engage users and encourage exploration. Working with the simulations strengthens understanding of key statistical ideas. There are also many examples, and detailed guidance to show readers how to analyze their own data using the new statistics, and practical strategies for interpreting the results. A particular strength of the book is its explanation of meta-analysis, using simple diagrams and examples. Understanding meta-analysis is increasingly important, even at undergraduate levels, because medicine, psychology and many other disciplines now use meta-analysis to assemble the evidence needed for evidence-based practice.
The book’s pedagogical program, built on cognitive science principles, reinforces learning:
Boxes provide "evidence-based" advice on the most effective statistical techniques. Numerous examples reinforce learning, and show that many disciplines are using the new statistics. Graphs are tied in with ESCI to make important concepts vividly clear and memorable. Opening overviews and end of chapter take-home messages summarize key points. Exercises encourage exploration, deep understanding, and practical applications.
This highly accessible book is intended as the core text for any course that emphasizes the new statistics, or as a supplementary text for graduate and/or advanced undergraduate courses in statistics and research methods in departments of psychology, education, human development , nursing, and natural, social, and life sciences. Researchers and practitioners interested in understanding the new statistics, and future published research, will also appreciate this book. A basic familiarity with introductory statistics is assumed.
Drawing on examples from across the social sciences, this book covers everything you need to know to plan, implement, and analyze the results of population-based survey experiments. But it is more than just a "how to" manual. This lively book challenges conventional wisdom about internal and external validity, showing why strong causal claims need not come at the expense of external validity, and how it is now possible to execute experiments remotely using large-scale population samples.
Designed for social scientists across the disciplines, Population-Based Survey Experiments provides the first complete introduction to this methodology.Offers the most comprehensive treatment of the subject Features a wealth of examples and practical advice Reexamines issues of internal and external validity Can be used in conjunction with downloadable data from ExperimentCentral.org for design and analysis exercises in the classroom
This expanded edition includes new data and easy-to-read graphics explaining the 2008 election. Red State, Blue State, Rich State, Poor State is a must-read for anyone seeking to make sense of today's fractured political landscape.
A black swan is a highly improbable event with three principal characteristics: It is unpredictable; it carries a massive impact; and, after the fact, we concoct an explanation that makes it appear less random, and more predictable, than it was. The astonishing success of Google was a black swan; so was 9/11. For Nassim Nicholas Taleb, black swans underlie almost everything about our world, from the rise of religions to events in our own personal lives.
Why do we not acknowledge the phenomenon of black swans until after they occur? Part of the answer, according to Taleb, is that humans are hardwired to learn specifics when they should be focused on generalities. We concentrate on things we already know and time and time again fail to take into consideration what we don’t know. We are, therefore, unable to truly estimate opportunities, too vulnerable to the impulse to simplify, narrate, and categorize, and not open enough to rewarding those who can imagine the “impossible.”
For years, Taleb has studied how we fool ourselves into thinking we know more than we actually do. We restrict our thinking to the irrelevant and inconsequential, while large events continue to surprise us and shape our world. In this revelatory book, Taleb explains everything we know about what we don’t know, and this second edition features a new philosophical and empirical essay, “On Robustness and Fragility,” which offers tools to navigate and exploit a Black Swan world.
Elegant, startling, and universal in its applications, The Black Swan will change the way you look at the world. Taleb is a vastly entertaining writer, with wit, irreverence, and unusual stories to tell. He has a polymathic command of subjects ranging from cognitive science to business to probability theory. The Black Swan is a landmark book—itself a black swan.
Praise for Nassim Nicholas Taleb
“The most prophetic voice of all.”—GQ
Praise for The Black Swan
“[A book] that altered modern thinking.”—The Times (London)
“A masterpiece.”—Chris Anderson, editor in chief of Wired, author of The Long Tail
“Idiosyncratically brilliant.”—Niall Ferguson, Los Angeles Times
“The Black Swan changed my view of how the world works.”—Daniel Kahneman, Nobel laureate
“[Taleb writes] in a style that owes as much to Stephen Colbert as it does to Michel de Montaigne. . . . We eagerly romp with him through the follies of confirmation bias [and] narrative fallacy.”—The Wall Street Journal
“Hugely enjoyable—compelling . . . easy to dip into.”—Financial Times
“Engaging . . . The Black Swan has appealing cheek and admirable ambition.”—The New York Times Book Review
From the Hardcover edition.
New to This Edition
*Updated throughout to incorporate important developments in latent variable modeling.
*Chapter on Bayesian CFA and multilevel measurement models.
*Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables.
*Utilizes the latest versions of major latent variable software packages.