Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. This item is unavailable.
Kohavi, Ron; Tang, Diane; Xu, Ya
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Language: English
Published by Cambridge University Press, 2020
- First Edition
- Softcover
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- Title
- Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing
- Author
- Kohavi, Ron; Tang, Diane; Xu, Ya
- Publisher
- Cambridge University Press
- Publication year
- 2020
- Condition
- Very Good
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1108724264
- ISBN 13
- 9781108724265
- Edition
- 1st Edition.
- Seller catalogs
- Instructional & Technical, Science & Technology
This practical guide for students, researchers and practitioners offers real world guidance for data-driven decision making and innovation.
"Synopsis" may belong to another edition of this title.
About the Author
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.
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.
"About the title" may belong to another edition of this title.
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