National Science Library of Georgia

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Trustworthy online controlled experiments : a practical guide to A/B testing / Ron Kohavi, Diane Tang, Ya Xu.

By: Contributor(s): Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2020Description: 1 online resource (xviii, 271 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781108653985 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 302.23/1 23
LOC classification:
  • HM741 .K68 2020
Online resources: Summary: 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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Title from publisher's bibliographic system (viewed on 13 Mar 2020).

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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