Classical Statistical Inference and A/B Testing in Python

The premise of this course is quite simple.

I asked myself: What is the most practical data science technique?

What do I use in the real-world most often?

Methods like neural networks and recommender systems are pretty application-specific, but statistical inference can be used for nearly everything.

• Website owners: which web page design leads to the highest engagement or revenue?
• Copywriters: which sales copy leads to the highest conversion rate?
• Online advertising platforms: which ads lead to the highest click-through rate?
• Clinical researchers and drug testers: which treatments, drugs, or therapies work best?
• Machine learning engineers and data scientists: which models have the best performance?

This course has 3 main parts:

• Maximum likelihood estimation review
• Confidence intervals
• Hypothesis testing

Each section prepares you for the next section, to yield maximum understanding and intuition.