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Interview Question: What is the goal of A/B testing in Data Science?
A/B testing, also known as split testing, is a basic randomised controlled experiment, used to compare two versions of a variable to find out which one performs better in a controlled environment. The data scientists endeavours to understand and measure the responses between each group that is being tested.
The test that can be performed to measure and understand the results of the A/B test is the two sample hypothesis t-test(or Independent samples t-test).
The two sample t-test is a method used to test whether the unknown population of two groups is equal or not. This test is used to analyse the results of an A/B test and determines whether the means of the two populations are equal.
To perform the two sample t-test, two variables are needed:-
- One variable defines the two groups
- The second variable is the measurement of interest
It is also necessary to have a hypothesis to perform the test. The hypothesis indicates that the two groups being tested are different.
To conduct a valid test:-
- Data values must be independent, i.e. measurements from one observation do not affect the measurements of the other.
- Data in each group must…
