"...a remarkably lucid, example driven text that anybody working near data would do well to read. ...Managers of data science teams stand to learn a great deal."
- D. Alex Hughes, PhD, Adjunct Assistant Professor, UC Berkeley School of Information
"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, Harvey Mudd College, Author and Mathemagician
"An excellent guide to what might go wrong as more and more businesses embrace data-driven decision-making."
- Avi Goldfarb, PhD, Rotman Chair in Artificial Intelligence and Healthcare.
"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."
- John P.A. Ioannidis, Stanford University
"Responsible data scientists should take heed of Smith and Cordes' guidance, especially when considering using AI in healthcare where transparency about safety, efficacy, and equity is life-saving."
- Michael Abramoff, MD, PhD, Founder and CEO of IDx
"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
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"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."
- Bill Chui, Director, GrandCare Health Services
"Smith and Cordes guide us through interesting accounts of the prairie dog holes of data analysis where the inexperienced often break their ankles. I read it in two sittings."
- Robert J. Marks II, Ph.D., Director, The Walter Bradley Center for Natural & Artificial Intelligence
"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 Depatrment, Cornell University
AAP 2020 Prose award winner
popular science & Popular Mathematics category
The 9 pitfalls of Data Science