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Applying Data Science Techniques to Business Problems Questions

Recognizing when A/B testing is appropriate vs observational analysis. Suggesting SQL queries or analysis approaches that would answer the business question. Understanding when you'd need advanced modeling vs simpler analysis. Connecting technical approaches to business decisions (e.g., 'This cohort analysis would tell us whether the decline is from existing users or new users').

MediumTechnical
69 practiced
Discuss the impact of missing data (user attributes or events) on experiment results and downstream modeling. Propose strategies such as multiple imputation, complete-case analysis, and weighting; explain trade-offs and outline a plan to test the robustness of conclusions to different missing-data assumptions.
MediumTechnical
113 practiced
Given events(user_id, event_date, revenue) and treatment(user_id, assigned boolean, assigned_at), outline an SQL-based approach to estimate incremental revenue attributable to treatment using matching or regression adjustment. Include pre-period baseline construction, matching logic, and assumptions and limitations of your approach.
MediumTechnical
68 practiced
Provide an example where adjusting for pre-treatment covariates in a regression increases precision of the treatment effect estimate. Show a sample regression specification and explain assumptions that justify covariate adjustment and diagnostics to check after fitting.
EasyTechnical
69 practiced
Explain in plain business language the difference between a p-value and a confidence interval. Use this example to illustrate: A/B test result shows p = 0.03 and 95% CI for uplift = [1.2%, 4.8%]. What do each of these convey to a product manager?
HardTechnical
72 practiced
A city implemented a policy affecting ride-hailing usage and randomization was not possible. Explain how you'd construct a synthetic control from other cities to estimate the policy effect: discuss donor-pool selection, predictor choice, optimization for weights, and inference using placebo tests.

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