Python development has had a great emergence in development of statistical packages, algorithms, and implementations. However, with the development and ease of practicing statistics & algorithms, there are still some rules and constraints one must follow to obtain quality solutions. And that is especially true with AB Testing, a statistical procedure to provide data-driven insights in uncertainty.
This will be a breakout Session on frequentist AB Testing in python.
We'll explore the jungle of application and statistical methodology and practice with examples of Click Through Rates, the early metrics of choice for AB Testing in production. That being said, compared to your last statistics course you may have taken in the past, there are still some rules and constraints one must follow to obtain quality solutions.