Explain P-Value and Errors in A/B Testing

##### Scenario You are advising on the design and analysis of an A/B test for a new feature. ##### Question Explain what a p-value represents in an experiment context. Define Type-I and Type-II errors with business examples. Describe Simpson’s Paradox and its danger in experiment readouts. How would you select primary, secondary, and guard-rail metrics? Name and briefly describe two causal-inference methods you would use if randomization were impossible. ##### Hints Cover hypothesis testing framework, practical significance, stratification, diff-in-diff, propensity scores.