Learn a simple way to use linear regression to create a synthetic control sample for your A/B test
A/B Testing is very powerful. I like this kind of experiment because it gives us the power to compare outcomes and determine if something is performing better than another.
A/B Testing has a specific type that adds the time component, which is the Before and After A/B Test. On that test, the comparison is between the situation of a given subject before and after an intervention.
Let us translate that previous sentence to a real-world example.
A company wants to know if an advertising would drive sales increase, so they can show that ad to a treatment group and compare the results to a control group that did not see the ad. The difference before and after the ad would indicate whether the intervention was effective or not.
Now, sometimes it is not possible to plan ahead and make that split of control and treatment groups before the intervention.
That is when the Synthetic Control sample will be useful. Using some statistics and machine learning, it is possible to simulate what would have happened with a sample if the…