Unit 8: Statistical Methods for Data Science

Unit 8 explores three different types of inferential statistics methods and examines their similarities and differences.

• Frequentist Inference: regards probability as the expected frequency of a particular outcome when an experiment is run multiple times.
• Bootstrap Inference: simulates reruns of an experiment to observe outcomes.
• Bayesian Inference: treats probability as a reflection of your belief in a specific outcome.

Learning Objectives

1. Develop an understanding of frequentist, Bootstrap, and Bayesian inference.
2. Peform Hypothesis testing to identify statistical significance.
3. Gain the ability to determine when a particular kind of statistical inference should be used over another.
4. Understanding how hypothesis testing is applied in real-world applicatins such as A/B testing.

Projects

Frequentist Inference:

• Part 1
• Part 2

Bootsrap Inference:

• Part 1

Bayesian Inference: