Week 4 | Module 3A | Experimentation in Data Science (A/B Testing and Statistical Analyses) I

Instructor: Roland Doku, Ph.D.

This topic covers the principles and applications of A/B testing, a foundational technique for making data-driven decisions in healthcare, business and various other industries. The session will focus on hypothesis testing, including the formulation of null and alternate hypotheses, and how they apply to experimental design. Attendees will learn about statistical concepts such as the central limit theorem, the distribution of sample means, and the importance of standard error in determining statistical significance. We will also explore how to calculate and interpret z-scores and t-scores, with a focus on understanding effect size, statistical power, and their relationship to sample size.