What is A/B testing and how do you design and analyze experiments?

A/B testing compares two versions to determine which performs better using statistical methods and experimental design principles.\n\n• Design: Define hypothesis, choose metrics, calculate sample size, randomize users\n• Implementation: Control group (A) vs treatment group (B), ensure proper isolation\n• Analysis: Statistical significance testing, confidence intervals, practical significance\n• Considerations: Multiple testing correction, external validity, business impact\n\nExample: Testing new website layout requires defining conversion rate hypothesis, calculating sample size for 80% power, randomly assigning users, running for sufficient duration, and using t-test or chi-square test to determine statistical significance.