The ultimate guide to A/B testing. Part 3: parametric tests

Maria Paskevich
Towards Data Science
6 min readNov 26, 2019

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A/B testing is a very popular technique for checking granular changes in a product without mistakenly taking into account changes that were caused by outside factors. In this series of articles, I will try to give an easy hands-on manual on how to design, run and estimate results of a/b tests, so you are ready to go and get these amazing statistically significant results!

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Data scientist at King.com, enthusiastic traveler, cat lover and unanimous coffee addict