Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Lära Metrics and Hypothesis | What is A/B Test?
A/B Testing in Python

book
Metrics and Hypothesis

Let's look at the steps of the A/B!

Let's talk briefly about the first 3 steps!

Goal setting

Before doing an A/B test, ask yourself a simple question:

'Why?'

Physicists set up experiments to learn more about natural phenomena, and products - to solve a problem or achieve a certain goal.

Metric definition

A/B testing is a quantitative study that reflects the change in what can be measured. It is essential to keep track of all the key metrics of the service since, as a result of the implementation of changes, one metric will increase while several others will decrease. Therefore, we need to understand what indicators we will consider or define as main metrics.

Hypotheses formulation

Let's try to put forward hypotheses for our test. This is a mandatory step in the A/B test. Later, we will test these hypotheses with basic knowledge of statistics to assess whether the results of the experiment tell us the truth. But more on that later!

question-icon

We will implement the new version of the button if we

___

Click or drag`n`drop items and fill in the blanks

dots
approve H1 hypothesis
dots
approve both hypothesis
dots
decline H1 hypothesis
dots
decline both hypothesis

Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 1. Kapitel 2

Fråga AI

expand
ChatGPT

Fråga vad du vill eller prova någon av de föreslagna frågorna för att starta vårt samtal

some-alt