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Vertrauenswürdige Online-kontrollierte Experimente: Ein praktischer Leitfaden für AB - GUT-
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eBay-Artikelnr.:127027882428
Artikelmerkmale
- Artikelzustand
- Brand
- Unbranded
- Book Title
- Trustworthy Online Controlled Experiments: A Practical Guide to
- MPN
- Does not apply
- ISBN
- 9781108724265
Über dieses Produkt
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
1108724264
ISBN-13
9781108724265
eBay Product ID (ePID)
2309818127
Product Key Features
Number of Pages
288 Pages
Publication Name
Trustworthy Online Controlled Experiments : a Practical Guide to A/B Testing
Language
English
Publication Year
2020
Subject
Web / Social Media, Databases / Data Mining, Web / User-Generated Content
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Height
0.6 in
Item Weight
14.1 Oz
Item Length
8.9 in
Item Width
6 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2019-042021
Dewey Edition
23
Reviews
'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 Ronny's work had on Bing and Microsoft, and I'm excited that these learnings can now reach a wider audience.' Harry Shum, Executive Vice President, Microsoft Artificial Intelligence and Research Group
Illustrated
Yes
Dewey Decimal
302.231
Table Of Content
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.
Synopsis
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., Getting numbers is easy; getting trustworthy numbers is hard. From experimentation leaders at Amazon, Google, LinkedIn, and Microsoft, this guide to accelerating innovation using A/B tests includes practical examples, pitfalls, and advice for students and industry professionals, plus deeper dives into advanced topics for experienced practitioners., 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.
LC Classification Number
HM741.K68 2020
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