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A/B Testing in Python
course content

Kursinnhold

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').

Oppgave

Swipe to start coding

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

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 3. Kapittel 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').

Oppgave

Swipe to start coding

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

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 3. Kapittel 8
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Vi beklager at noe gikk galt. Hva skjedde?
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