Winner of the 2020 Prose Award for Excellence in Popular Science & Popular Mathematics by the Association of American Publishers
Gary Smith is the Fletcher Jones Professor of Economics at Pomona College. He received his Ph.D. in Economics from Yale University and was an Assistant Professor there for seven years. He has won two teaching awards and written (or co-authored) more than 80 academic papers and twelve books including Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie With Statistics, What the Luck? The Surprising Role of Chance in Our Everyday Lives, and Money Machine: The Surprisingly Simple Power of Value Investing. His research has been featured by Bloomberg Radio Network, CNBC, The Brian Lehrer Show, Forbes, The New York Times, Wall Street Journal, Motley Fool, Newsweek, and BusinessWeek. Jay Cordes is a data scientist who enjoys tackling challenging problems, including how to guide future data scientists away from the common pitfalls he saw in the corporate world. He's a recent graduate from UC Berkeley's Master of Information and Data Science (MIDS) program and graduated from Pomona College with a mathematics major. He has worked as a software developer and a data analyst and was also a strategic advisor and sparring partner for the winning pokerbot in the 2007 AAAI Computer Poker Competition world championship.
Gary Smith and Jay Cordes have a most captivating way and special
talent to describe how easy it is to be fooled by the promises of
spurious data and by the hype of data science.
*Professor John P.A. Ioannidis, Scientist, Stanford University,
"the godfather of science reform" (Wired), "one of the most
influential scientists alive" (Atlantic)*
Using fascinating personal anecdotes and eye-opening historical
accounts, Smith and Cordes guide us through interesting accounts of
the prairie dog holes of data analysis where the unexperienced
often break their ankles. I read it in two sittings.
*Robert J. Marks II, Ph.D., Distinguished Professor of Electrical &
Computer Engineering, Baylor University, Director, The Walter
Bradley Center for Natural & Artificial Intelligence*
Smith and Cordes have produced a remarkably lucid, example-driven
text that anybody working near data would do well to read. Though
the book is presented as fables and pitfalls, a cogent, scientific
approach reveals itself. Managers of data science teams stand to
learn a great deal; seasoned data scientists will nod their heads
knowingly.
*D. Alex Hughes, Adjunct Assistant Professor, UC Berkeley School of
Information*
Whether you manage a data science team or rely on data science to
make critical decisions, this book illustrates how easy it is to
draw wrong conclusions that appear to be supported by data. Gary
Smith and Jay Cordes have written this must-read book for anyone
who wants to avoid falling victim to the pitfalls, and make
data-driven decisions with confidence.
*Bill Chui, Director, GrandCare Health Services*
The current AI hype can be disorienting, but this refreshing book
informs to realign expectations, and provides entertaining and
relevant narrative examples that illustrate what can go wrong when
you ignore the pitfalls of data science. Responsible data
scientists should take heed of Smith and Cordes' guidance,
especially when considering usingAI in healthcare where
transparency about safety, efficacy, and equity is life-saving.
*Michael Abramoff, MD, PhD, Founder and CEO of Idx, Watzke
Professor of Ophthalmology and Visual Sciences at the University of
Iowa*
In this era of big data, it's good to have a book that collects
ways that big data can lie and mislead. This book provides
practical advice for users of big data in a way that's easy to
digest and appreciate, and will help guide them so that they can
avoid its pitfalls.
*Joseph Halpern, Joseph C. Ford Professor of Engineering, Computer
Science Department, Cornell University*
Increasingly, the world is immersed in data! Gary Smith and Jay
Cordes offer up a veritable firehose of fabulous examples of the
uses/misuses of all that "big data" in real life. You will be a
more informed citizen and better-armed consumer by reading their
book... and, it couldn't come at a better time!
*Shecky Riemann, math blogger*
An excellent guide to what might go wrong as more and more
businesses embrace data-driven decision-making.
*Avi Goldfarb, author of Prediction Machines*
The 9 Pitfalls of Data Science is the modern version of the classic
book, How to Lie with Statistics. The authors write with authority,
experience, and humor and makes for a very enjoyable and
informative reading experience.
*Arthur Benjamin, Professor of Mathematics, Harvey Mudd College,
Author of The Magic of Math: Solving for X and Figuring Out Why*
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