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Lære Now We Can Answer | The First A/B Test
A/B Testing in Python

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Now We Can Answer

This chapter will help us to answer the question 'Can we believe that the variant of the site will help us to increase in clicks?'

So, we have studied how do 2 groups' distributions look like:

  • Their plots don't look similar;

  • Their confidence intervals don' cover each other a lot.

Earlier, we decided that we were going to use t-criterion criterion to cope with our problem. It is our last check to prove whether there is a NON-RANDOM difference between groups.

To perform the t-test use scipy.stats.ttest_ind(control_group_data, test_group_data).

Oppgave

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  1. Perform the t-test.

Løsning

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book
Now We Can Answer

This chapter will help us to answer the question 'Can we believe that the variant of the site will help us to increase in clicks?'

So, we have studied how do 2 groups' distributions look like:

  • Their plots don't look similar;

  • Their confidence intervals don' cover each other a lot.

Earlier, we decided that we were going to use t-criterion criterion to cope with our problem. It is our last check to prove whether there is a NON-RANDOM difference between groups.

To perform the t-test use scipy.stats.ttest_ind(control_group_data, test_group_data).

Oppgave

Swipe to start coding

  1. Perform the t-test.

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!

close

Awesome!

Completion rate improved to 4.55

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