When a poll says "margin of error ±3%," that number only captures sampling error — not the real-world mess of non-response bias, weighting assumptions, and demographic guesswork. In this episode, we break down how modern polling actually constructs representative samples: from random-digit dialing's collapse to address-based sampling, from demographic weighting to the "assumption of ignorability" that makes or breaks a survey. Along the way, we explore what 2016's polling miss taught us about weighting by the wrong variables, why opt-in panels like YouGov are still controversial, and why "representative enough" is a far more honest question than any pollster will admit.
Episode 2875 — myweirdprompts.com/n/2875 (permanent short link: myweirdprompts.com/001454)
