Walk through an A/B test end-to-end

Walk through how you would design, run, and analyze an **A/B test** for a product change. Your answer should include: - Hypothesis framing and choosing **primary**, **diagnostic**, and **guardrail** metrics. - Experiment design: unit of randomization, population, exposure definition, duration, and handling novelty/seasonality. - How you determine **sample size / MDE / power**. - Data quality checks (e.g., SRM), logging issues, and how you validate randomization. - Statistical analysis approach (confidence intervals, p-values, multiple testing, sequential peeking). - How you interpret results and make a launch decision, including practical vs statistical significance. - Common pitfalls (e.g., interference/network effects, noncompliance, missing data).