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A/B Test

An A/B test is a randomized controlled experiment that simultaneously exposes two groups of users to a control variant (A) and a treatment variant (B) in order to determine whether a measured outcome differs significantly between them. The modern online controlled experiment framework was systematized by Ron Kohavi and colleagues at Microsoft in the early 2000s, building on R. A. Fisher's classical randomization principles from 1935. It is the dominant causal inference tool in web product development, digital marketing, and experimentation platforms.

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A/B Test (Online Controlled Experiment)

Taxonomisk metodpost · hypothesis-test / experimental-design

Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. · ISBN 9781108724265
Deng, A., Xu, Y., Kohavi, R., & Walker, T. (2013). Improving the Sensitivity of Online Controlled Experiments by Utilizing Pre-Experiment Data. KDD '13. · URL

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