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Often abbreviated DID or DD, this is a technique for inferring causality from observational data. It involves comparing measurements before and after a treatment occurs (hence, the growth rate) in both a group that received the treatment, and an otherwise comparable group that did not.

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What is the difference between difference-in-difference (DiD) and A/B testing?

The only difference is what group's lexicon the term belongs to (DiD is the term used by economists, while A/B testing is the term used by software/UX). Both terms refer to randomized trials where the …
liangjy's user avatar
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