Getting numbers is easy; getting numbers you can trust is hard. This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests.
"A/B testing is the gold standard of creating verifiable and repeatable experiments, and   this book is its definitive text  " --   Steve Blank  , father of modern entrepreneurship, author of The Startup Owner's Manual and The Four Steps to the Epiphany
"This book is a   great resource for executives, leaders, researchers or engineers   looking to use online controlled experiments" --   Harry Shum  , Executive Vice President, Microsoft Artificial Intelligence and Research Group
"A great book that is both   rigorous and accessible  . Readers will learn how to bring trustworthy controlled experiments, which have   revolutionized internet product development  , to their organizations" --   Adam D'Angelo  , Co-founder and СЕО (Поисковая оптимизация SEO of Quora and prior CTO of Facebook 
"Kohavi, Tang and Xu have a   wealth of experience and excellent advice   to convey, so the book has lots of practical real world examples and lessons learned over many years of the application of these techniques at scale." --   Jeff Dean  , Google Senior Fellow, and SVP, Google Research
"  The secret sauce   for a successful online business is experimentation. But it is a secret no longer. Here three   masters of the art   describe the ABCs of A/B testing so that you too can continuously improve your online services." --   Hal Varian  , Chief Economist, Google, and author of Intermediate Microeconomics: A Modern Approach
"This is   the new bible   of how to get from data to decisions in the digital age." --   Scott Cook  , Intuit Co-founder & Chairman of the executive committee
Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to
[*]          Use the scientific method to evaluate hypotheses using controlled experiments.
[*]          Define key metrics and ideally an Overall Evaluation Criterion.
[*]          Test for trustworthiness of the results and alert experimentersto violated assumptions.
[*]          Build a scalable platform that lowers the marginal cost of experiments close to zero.
[*]          Avoid pitfalls like carryover effects and Twyman's law * Understand how statistical issues play out in practice.

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