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Experimentation Methodology and Rigor Questions

Focuses on rigorous experimental methodology and advanced testing approaches needed to produce reliable, actionable results. Topics include statistical power and minimum detectable effect trade offs, multiple hypothesis correction, sequential and interim analysis, variance reduction techniques, heterogenous treatment effects, interference and network effects, bias in online experiments, two stage or multi component testing, multivariate designs, experiment velocity versus validity trade offs, and methods to measure business impact beyond proximal metrics. Senior level discussion includes designing frameworks and practices to ensure methodological rigor across teams and examples of how to balance rapid iteration with safeguards to avoid false positives.

MediumTechnical
67 practiced
You are testing two components simultaneously (pricing and UI) expected to interact. Design an experiment and analysis plan to measure main effects and interactions: choose between factorial design, two-stage testing, or sequential component testing; compute sample size considerations for interaction detection; and explain how you'd interpret interaction terms for product decisions.
HardTechnical
119 practiced
You have 10 concurrent experiments that may interact (same users can be exposed to different tests). Propose an experimental design and analysis strategy to detect and account for interactions between experiments, balancing traffic efficiency and validity. Discuss blocking, orthogonalization, and analytical interaction modeling.
MediumTechnical
74 practiced
Discuss common sources of measurement bias in online experiments (instrumentation bugs, denominator issues, delayed events, bots, sampling biases). For each source propose detection methods and corrective actions you would implement in a production experimentation system.
EasyTechnical
78 practiced
What is the Stable Unit Treatment Value Assumption (SUTVA)? Explain its two components and give real-world examples in online products where SUTVA is violated and why that matters for A/B test interpretation.
MediumTechnical
79 practiced
You must decide between running a classic A/B test or using a multi-armed bandit for a high-traffic product promotion expected to produce quick wins. Compare advantages and disadvantages of bandits vs fixed-horizon A/B tests in terms of speed, regret, ability to measure long-term metrics, and statistical inference. Provide rules for when to prefer each approach.

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