'At the core of the Lean Methodology is the scientific method: Creating hypotheses, running experiments, gathering data, extracting insight and validation or modification of the hypothesis. A/B testing is the gold standard of creating verifiable and repeatable experiments, and this book is its definitive text.' Steve Blank, Adjunct professor at Stanford University, 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 to optimize product features, project efficiency or revenue. I know firsthand the impact that Kohavi's work had on Bing and Microsoft, and I'm excited that these learnings can now reach a wider audience.' Harry Shum, EVP, 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 former CTO of Facebook

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'This book is a great overview of how several companies use online experimentation and A/B testing to improve their products. 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

'Do you want your organization to make consistently better decisions? This is the new bible of how to get from data to decisions in the digital age. Reading this book is like sitting in meetings inside Amazon, Google, LinkedIn, Microsoft. The authors expose for the first time the way the world's most successful companies make decisions. Beyond the admonitions and anecdotes of normal business books, this book shows what to do and how to do it well. It's the how-to manual for decision-making in the digital world, with dedicated sections for business leaders, engineers, and data analysts.' Scott Cook, Intuit Co-founder & Chairman of the Executive Committee

'Online controlled experiments are powerful tools. Understanding how they work, what their strengths are, and how they can be optimized can illuminate both specialists and a wider audience. This book is the rare combination of technically authoritative, enjoyable to read, and dealing with highly important matters.' John P. A. Ioannidis, Stanford University

'Kohavi, Tang, and Xu are pioneers of online experimentation. The platforms they've built and the experiments they've enabled have transformed some of the largest internet brands. Their research and talks have inspired teams across the industry to adopt experimentation. This book is the authoritative yet practical text that the industry has been waiting for.' Adil Aijaz, Co-founder and CEO, Split Software

'Which online option will be better? We frequently need to make such choices, and frequently err. To determine what will actually work better, we need rigorous controlled experiments, aka A/B testing. This excellent and lively book by experts from Microsoft, Google, and LinkedIn presents the theory and best practices of A/B testing. A must read for anyone who does anything online!' Gregory Piatetsky-Shapiro, Ph.D., president of KDnuggets, co-founder of SIGKDD, and LinkedIn Top Voice on Data Science & Analytics

'Ron Kohavi, Diane Tang and Ya Xu are the world's top experts on online experiments. I've been using their work for years and I'm delighted they have now teamed up to write the definitive guide. I recommend this book to all my students and everyone involved in online products and services.' Erik Brynjolfsson, Massachusetts Institute of Technology, co-author of The Second Machine Age

'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, New York University and co-author of the best-selling Data Science for Business

'In the past two decades the technology industry has learned what scientists have known for centuries: that controlled experiments are among the best tools to understand complex phenomena and to solve very challenging problems. The ability to design controlled experiments, run them at scale, and interpret their results is the foundation of how modern high tech businesses operate. Between them the authors have designed and implemented several of the world's most powerful experimentation platforms. This book is a great opportunity to learn from their experiences about how to use these tools and techniques.' Kevin Scott, EVP and CTO of Microsoft

'Online experiments have fueled the success of Amazon, Microsoft, LinkedIn and other leading digital companies. This practical book gives the reader rare access to decades of experimentation experience at these companies and should be on the bookshelf of every data scientist, software engineer and product manager.' Stefan Thomke, William Barclay Harding Professor, Harvard Business School, author of Experimentation Works: The Surprising Power of Business Experiments

'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

'Experiments are the best tool for online products and services. This book is full of practical knowledge derived from years of successful testing at Microsoft Google and LinkedIn. Insights and best practices are explained with real examples and pitfalls, their markers and solutions identified. I strongly recommend this book!' Preston McAfee, former Chief Economist and VP of Microsoft

'Experimentation is the future of digital strategy and 'Trustworthy Experiments' will be its Bible. Kohavi, Tang and Xu are three of the most noteworthy experts on experimentation working today and their book delivers a truly practical roadmap for digital experimentation that is useful right out of the box. The revealing case studies they conducted over many decades at Microsoft, Amazon, Google and LinkedIn are organized into easy to understand practical lessens with tremendous depth and clarity. It should be required reading for any manager of a digital business.' Sinan Aral, David Austin Professor of Management, Massachusetts Institute of Technology, and author of The Hype Machine

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. 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 experimenters to 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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Preface – how to read this book; 1. Introduction and motivation; 2. Running and analyzing experiments: an end-to-end example; 3. Twyman's law and experimentation trustworthiness; 4. Experimentation platform and culture; Part II: 5. Speed matters: an end-to-end case study; 6. Organizational metrics; 7. Metrics for experimentation and the Overall Evaluation Criterion (OEC); 8. Institutional memory and aeta-analysis; 9. Ethics in controlled experiments; Part III: 10. Complementary techniques; 11. Observational causal studies; Part IV: 12. Client-side experiments; 13. Instrumentation; 14. Choosing a randomization unit; 15. Ramping experiment exposure: trading off speed, quality, and risk; 16. Scaling experiment analyses; Part V: 17. The statistics behind online controlled experiments; 18. Variance estimation and improved sensitivity: pitfalls and solutions; 19. The A/A test; 20. Triggering for improved sensitivity; 21. Guardrail metrics; 22. Leakage and interference between variants; 23. Measuring long-term treatment effects.
Les mer
'At the core of the Lean Methodology is the scientific method: Creating hypotheses, running experiments, gathering data, extracting insight and validation or modification of the hypothesis. A/B testing is the gold standard of creating verifiable and repeatable experiments, and this book is its definitive text.' Steve Blank, Adjunct professor at Stanford University, father of modern entrepreneurship, author of The Startup Owner's Manual and The Four Steps to the Epiphany
Les mer
This practical guide for students, researchers and practitioners offers real world guidance for data-driven decision making and innovation.

Produktdetaljer

ISBN
9781108724265
Publisert
2020-04-02
Utgiver
Vendor
Cambridge University Press
Vekt
420 gr
Høyde
226 mm
Bredde
152 mm
Dybde
14 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
288

Biographical note

Ron Kohavi is a Technical Fellow and corporate VP of Microsoft's Analysis and Experimentation, and was previously director of data mining and personalization at Amazon. He received his Ph.D. in Computer Science from Stanford University. His papers have over 40,000 citations and three of them are in the top 1,000 most-cited papers in Computer Science. Diane Tang is a Google Fellow, with expertise in large-scale data analysis and infrastructure, online controlled experiments, and ads systems. She has an A.B. from Harvard and an M.S./Ph.D. from Stanford University, with patents and publications in mobile networking, information visualization, experiment methodology, data infrastructure, data mining, and large data. Ya Xu heads Data Science and Experimentation at LinkedIn. She has published several papers on experimentation and is a frequent speaker at top-tier conferences and universities. She previously worked at Microsoft and received her Ph.D. in Statistics from Stanford University.