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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).

Opgave

Swipe to start coding

  1. Perform the t-test.

Løsning

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Sektion 2. Kapitel 7
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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).

Opgave

Swipe to start coding

  1. Perform the t-test.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

close

Awesome!

Completion rate improved to 4.55

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