{"blocks": [{"key": "97fa47aa", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "f8ae301c", "text": "You are responsible for evaluating the lift of a new recommendation algorithm via online experiments.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "c938b081", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "17ff15c3", "text": "Design an A/B test to measure the algorithm’s impact on revenue: define hypotheses, choose unit of randomization, compute required sample size, and detail success metrics. After the experiment you obtain p = 0.08 for revenue lift; interpret this result and recommend whether to ship. Explain how you would estimate causal impact if randomization were not possible; compare methods such as difference-in-differences, propensity score matching, and instrumental variables.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "f7214fe9", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "1be356ad", "text": "Demonstrate knowledge of hypothesis testing, power analysis, Type I/II errors, and causal inference techniques.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}