Implementing A/B Tests in Python
A/B testing is one of the most important tools for optimizing most things we interact with on our computers, phones and tablets. From website layouts to social media ads and product features, every button, banner and call to action has probably been A/B tested. And these tests can be extremely granular; Google famously tested "40 shades of blue" to decide what shade of blue should be used for links on the Google and Gmail landing pages.
I recently completed the Udacity course "A/B Testing by Google - Online Experiment Design and Analysis" and wanted to share some of my key takeaways as well as how you can implement A/B testing using Python.
Data source: https://www.kaggle.com/zhangluyuan/ab-testing