##### Scenario You are analyzing user engagement on a short-video sharing product. The team needs statistical insights into how views and shares behave across users and videos. ##### Question 1. Given a distribution of video views, how would you compute, interpret, and compare its **mode**, **median**, and **mean**? What relationship do you expect between them for this kind of data, and which should you report? 2. Each video a user watches has a **10% chance** of being shared. What is the probability that **at least one** of ten independently watched videos is shared? 3. You observe that **average watch length per video is increasing while the average share count (share rate) per video is decreasing**. Propose possible hypotheses for this divergence and outline how you would test them, distinguishing causal from correlational explanations. ##### Hints Apply descriptive statistics for skewed distributions, binomial probability, and a structured causal/experimental-design framework for diagnosing a metric divergence.