Confidence Intervals, p‑Values, and Caveats: Regulator‑Ready Statistical Phrasing for ML Claims
Struggling to turn model results into claims that survive FDA/EMA review? In this lesson, you’ll learn to phrase ML performance using confidence intervals, p-values, and explicit hypothesis frameworks that are specific, bounded, and decision-linked—ready for SaMD dossiers across US/EU. You’ll find concise explanations, regulator‑calibrated examples, and targeted exercises that reinforce compliant language, caveats, and thresholds. Finish with a reusable template that standardizes your team’s voice, reduces queries, and accelerates review cycles.
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