Kursusindhold
A/B Testing in Python
A/B Testing in Python
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!
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