{"blocks": [{"key": "6d4a7856", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "bc347367", "text": "You are a data scientist advising a product team on statistical analysis and experimental design.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "35af5f60", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "899d73c8", "text": "Explain Simpson’s paradox and illustrate it with a concrete numeric example understandable to a non-technical PM. In a forest with three bird species, propose and define metrics that quantify how segregated the species are from one another. A simple linear regression is run to estimate the effect of YouTube ad impressions on product sales. What potential statistical problems do you see and how would you redesign the study? Name ways to reduce a survey’s margin of error. If sample size and confidence level cannot change, what else could you do and why might bootstrap methods help?", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "bff8bcd7", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "1d03146b", "text": "Discuss confounding, omitted‐variable bias, experimental control, effect size, confidence intervals, and resampling logic in plain language.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}