The Twitter Engineering Blog

Information from Twitter's engineering team about our technology, tools and events.

Posts from Engineering: A/B testing

Power, minimal detectable effect, and bucket size estimation in A/B tests

Figuring out the minimal number of users one must expose to an experimental treatment to collect actionable data is not a trivial task. We explain how we approach this problem with Twitter’s A/B testing platform (DDG), and how we communicate issues of statistical power to experimenters.

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