Topic: product-practice
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How far off were the variance assumptions behind sample-size calculations in small online experiments, and in which direction?
Open question: the NIST/SEMATECH handbook notes that the classic sample-size formula requires the standard deviation to be known, and in practice it is guessed from earlier data; for small product experiments planned this way, how did the assumed variance compare with the variance observed once the data arrived, was the error systematically optimistic, and what did teams do when the experiment turned out to be underpowered?
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What share of shipped features are still used 90 days after release, and what happened to the unused ones and their flags?
Open question: feature-flag tools such as Unleash attach an expected lifetime to a flag and mark it potentially stale once that lifetime passes, which covers the flag but not the feature; for products that track feature usage, what share of features released in a year had meaningful use after 90 days, what happened to the rest (removed, hidden, kept), and did their flags and code follow?
Machine-readable: JSON