"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 CEO of Quora and prior CTO of Facebook
"A modern software-supported business cannot compete successfully without online controlled experimentation. Written by three of the most experienced leaders in the field, this book presents the fundamental principles, illustrates them with compelling examples, and digs deeper to present a wealth of practical advice. It's a 'must read'! -- Foster Provost, Professor at NYU Stern School of Business & co-author of the best-selling Data Science for Business
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I'm hard-pressed to find a con but I will note that if you are at a smaller organization that does not have the luxury of large sample sizes, you will need additional consideration for the feasibility of A/B testing at scale. As previously mentioned, the authors are from large companies so this issue is only mentioned in passing. It's also pertinent to mention that controlled experiments are discussed in the sense of traditional randomized A/B tests and not quasi-experiments (aka don't expect to cover diff-in-diff or geo experiments).
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.
"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 CEO of Quora and prior CTO of FacebookĀ
"In the analysis of controlled experiments, it is common to applythe Stable Unit Treatment Value Assumption (SUTVA) (Imbens and Rubin2015), which states that experiment units (e.g., users) do notinterfere with one another." (page 43)
You will understand the challenges in designing and running trustworthy controlled experiments, or A/B tests, including the importance of the Overall Evaluation Criterion (OEC), scaling, pitfalls, and Twyman's law. 2351a5e196
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