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-testusescipy.stats.ttest_ind(control_group_data, test_group_data).
Swipe to start coding
- Perform the
t-test.
Oplossing
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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-testusescipy.stats.ttest_ind(control_group_data, test_group_data).
Swipe to start coding
- Perform the
t-test.
Oplossing
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Awesome!
Completion rate improved to 4.55single
