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Research Design and Study Planning Questions

End to end planning and design of research studies to rigorously answer product, user experience, or scientific questions. Candidates should be able to translate business or product problems into clear and testable research questions and hypotheses and convert those questions into feasible and valid study plans. Core skills include selecting appropriate qualitative, quantitative, or mixed methods, defining primary outcomes and success metrics, aligning sampling strategy and inclusion and exclusion criteria, estimating sample sizes and articulating precision and power considerations, designing recruitment approaches and consent procedures, drafting interview guides survey items and measurement instruments with attention to reliability and validity, planning data collection workflows and quality controls, and outlining statistical and qualitative analysis plans and integration strategies for mixed methods. Candidates should also be able to identify potential confounds and threats to internal and external validity and propose mitigation approaches, scope studies to remain feasible under time and resource constraints, plan logistics timelines and resource allocation, pilot and iterate instruments, address ethical and regulatory requirements such as institutional review board review and data privacy, and communicate research plans limitations and actionable findings to stakeholders. Interviewers may probe trade offs among methodologies bias mitigation strategies reproducibility and documentation practices how the candidate managed scope and stakeholder expectations and how preliminary findings or stakeholder input influenced the evolution of research questions and study scope while avoiding scope creep.

HardTechnical
0 practiced
Stakeholders demand fast answers but insist on high rigor. Describe a concrete negotiation and communication strategy you would use to reconcile these conflicting priorities. Outline a minimal viable study (MVS) you could deliver quickly that preserves core validity, list limitations you would document, provide example phrasing for communicating uncertainty, and describe how you would plan follow-up studies to increase rigor over time.
HardTechnical
0 practiced
Design a measurement strategy for the latent construct 'collaborative-intent' across multiple countries. Describe item-generation steps, cognitive testing, pilot sampling, whether to use Item Response Theory (IRT) or Classical Test Theory (CTT), procedures for cross-cultural validation (including translation/back-translation), and approaches to detect and handle Differential Item Functioning (DIF).
HardTechnical
0 practiced
Compare multi-armed bandit (MAB) adaptive experiments with fixed randomized controlled trials. For a high-traffic e-commerce homepage, discuss when you would prefer adaptive allocation (contextual bandits) over a traditional RCT, including trade-offs in regret minimization vs unbiased estimation, consequences for treatment effect estimation and heterogeneity, statistical guarantees under adaptive allocation, and operational challenges in implementation and inference.
HardTechnical
0 practiced
Provide the formula and explanation for sample size calculation in a cluster-randomized trial with equal cluster sizes for detecting a difference in means given desired power, ICC, cluster size m, and effect size. Explain the design effect (inflation factor), adjustments required for variable cluster sizes (coefficient of variation), and describe practical ways to estimate ICC from limited pilot data.
EasyTechnical
0 practiced
Describe the core elements you'd include in an Institutional Review Board (IRB) or ethics submission for a user research study that includes an in-app survey and optional follow-up interviews. Cover risk assessment, consent language, compensation, data retention and deletion, de-identification measures, data access controls, and special procedures if minors might be present.

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