Explore the fundamentals of online experimentation and A/B testing in this comprehensive 2-hour lecture from Data Science Dojo's bootcamp. Delve into best practices for designing and evaluating A/B and multi-variate tests, learn to choose appropriate metrics, detect and avoid errors, and properly interpret test results. Cover topics including the Obama campaign's use of A/B testing, applications in email marketing and online forms, the differences between A/B and multivariate testing, control and treatment groups, hypothesis formulation, confidence intervals, and A/A testing. Gain insights into practical tools and participate in a Q&A session to enhance your understanding of this crucial data science technique.
Introduction to Online Experimentation and A-B Testing
Overview
Syllabus
– Intro
– A/B testing
– Obama campaign
– A/B testing on emails and newsletters
– Online forms
– Why do we use A/B testing?
– A/B testing versus multivariate testing
– Control and treatment
– Metrics
– Hypothesis
– Confidence Intervals
– A/A testing
– Metrics
– Tools
– QnA
Taught by
Data Science Dojo
