{"blocks": [{"key": "0c3871d0", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "cc742122", "text": "Ads team wants to understand click behaviour and validate statistical knowledge during an analytical-execution round.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "509f9e6b", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "25159d2e", "text": "Name three probability distributions suitable for modeling ad clicks and state the core assumption of each. Write the expectation and variance formula for those distributions. If 90 % of users are high-intent and 10 % are low-intent, each with an expected click-through of 0.30, compute the overall expected CTR. Sketch the PDF of an exponential distribution and describe what happens to its shape as sample size becomes very large.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "ad5c8d0d", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "aa8c97cc", "text": "Think Bernoulli, Binomial, Poisson, Exponential; use law of total expectation; recall CLT.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}