> We have coped with the easy variant of the A/B test. Now we will cope with another A/B test where we will receive another distribution, and we will use another criterion.

Before moving to the next, please, study what data you receive during the 14 days of the A/B test.

|**Column name**|**What's inside?**|
|---|---|
|`user_id`| the user id | 
|`date`| the date the user visited the page | 
|`group`| the group name (control/test) | 
|`platform`| the platform the user is using | 
|`device_type`| the device type | 
|`first_visit_after_test_start`| whether the user visited the site for the first time or not | 
|`contact_views_number`| the number of clicks on the control/test button | 
|`start_chats_number`| the number of clicks in the 'Chat' button | 

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!'.

Column name	What's inside?
`user_id`	the user id
`date`	the date the user visited the page
`group`	the group name (control/test)
`platform`	the platform the user is using
`device_type`	the device type
`first_visit_after_test_start`	whether the user visited the site for the first time or not
`contact_views_number`	the number of clicks on the control/test button
`start_chats_number`	the number of clicks in the 'Chat' button

A/B Testing in Python

Data Study