A/B Testing Intuition Busters-Reference-Cited by-同舟云学术

A/B Testing Intuition Busters

Published:2022-08-14 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Kohavi Ron¹,Deng Alex²,Vermeer Lukas³

Affiliation:

1. Kohavi, Los Altos, CA, USA

2. Airbnb Inc, Seattle, WA, USA

3. Vista, Delft, Netherlands

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539160

Reference48 articles.

1. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations

2. Top Challenges from the first Practical Online Controlled Experiments Summit. Gupta, Somit, et al. 1 , June 2019 , Vol. 21 . Top Challenges from the first Practical Online Controlled Experiments Summit. Gupta, Somit, et al. 1, June 2019, Vol. 21.

3. Seven pitfalls to avoid when running controlled experiments on the web

4. Pitfalls of long-term online controlled experiments. Dmitriev, Pavel, et al. Washington, DC : s.n., 2016 . IEEE International Conference on Big Data. pp. 1367 -- 1376 . Pitfalls of long-term online controlled experiments. Dmitriev, Pavel, et al. Washington, DC : s.n., 2016. IEEE International Conference on Big Data. pp. 1367--1376.

5. Trustworthy Online Controlled Experiments

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