{"blocks": [{"key": "da9fb1f5", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "c05d0b23", "text": "An advertiser is running campaigns on Facebook and wants to know whether the ads increased conversions compared with an unexposed control group.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "0079ee5e", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "33b56543", "text": "Given conversion counts and exposures for test and control groups, how would you estimate the lift and its statistical significance? How large a sample is required to detect a 5% lift at 90% power? If the London stakeholder asks for a Bayesian approach, how would you re-frame the analysis?", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "95307b65", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "67990d8e", "text": "Two-proportion z-test or Bayesian posterior for lift; power calculation formula.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}