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A/B Testing in Python
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Course Content

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

book
What to Do with the Button

It's time to answer the main question! Note that we chose the Mann-Whitney criterion for this A/B test.

Use scipy.stats.mannwhitneyu(control_group_data, test_group_data, alternative = 'greater').

Task

Swipe to start coding

  1. Perform the statistical analysis with the Mann-Whitney criterion.

Solution

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SectionΒ 3. ChapterΒ 8
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book
What to Do with the Button

It's time to answer the main question! Note that we chose the Mann-Whitney criterion for this A/B test.

Use scipy.stats.mannwhitneyu(control_group_data, test_group_data, alternative = 'greater').

Task

Swipe to start coding

  1. Perform the statistical analysis with the Mann-Whitney criterion.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 3. ChapterΒ 8
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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