> 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)`.

A/B test is one of the critical decisions when implementing something new in the IT sphere. It is the right time to get acquainted with this test!

In this section, we will learn some preparation things that are held before the A/B test.

In this section, we will perform our first A/B test. An easy version of the A/B test will help us to practice without difficulties!

It is time to meet the real A/B test. In this section, we will train ourselves using the knowledge we received during the two previous sections. After studying this section, you can say: 'I know what the A/B test is!'.

Now We Can Answer

Solução