Explain P-value, Confidence Interval, and Multiple Testing Adjustments
AmazonData Scientist · Technical Screen
Last updated
Evaluates A/B testing inference fundamentals, including p-values, confidence intervals, multiple testing adjustments, Type I and Type II errors, z-tests versus t-tests, and CLT versus LLN. Strong answers connect definitions to experiment decisions and common pitfalls.
Scenario
AB-testing and inferential statistics for new product launches.
Question
Define p-value and confidence interval and explain their relationship. How do you adjust for multiple testing (e.g., Bonferroni, Tukey)? Explain Type I and Type II errors with examples. When would you use a Z-test versus a t-test? Compare the Central Limit Theorem with the Law of Large Numbers.
Hints
Focus on assumptions, formulas, and practical implications.
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