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A/B Testing in Python
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A/B Testing in Python

A/B Testing in Python

1. What is A/B Test?
A/B Test and our GoalMetrics and HypothesisHow Not to Fail a Test
2. The First A/B Test
Data StudyWhat Criterion to ChooseCriterionControl and Test GroupsPlots to CompareIntervals to CompareNow We Can AnswerTo Sum Up
3. Performing One More AB Test
Data StudyPreparationPreprocessing DataChoosing the CriterionCriterionDividing into GroupsComparing GroupsWhat to Do with the ButtonPink or Blue?Upd MetricFinish

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Criterion

We have checked our distribution by showing it as a distplot, a qqplot, and by performing a normaltest. Let's compare normal plots and what we received to decide what distribution we have.

From the previous chapter, we learned that if the normaltest shows the value > 0.05, the distribution is normal.

As we have a normal distribution, our criterion will be a t-criterion (Student's criterion).

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Section 2. Chapitre 3
Nous sommes désolés de vous informer que quelque chose s'est mal passé. Qu'est-il arrivé ?
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