The Power and the Problem With the P-Value | Understanding Medical Research

The P-value decides whether a medical study counts as significant, and it is misread constantly. This video covers what the P-value actually measures, why 0.05 is arbitrary, why statistical significance is not clinical significance, and why prior probability shapes the interpretation. Chapters: 00:00 Goals and a suspicious quarter 03:09 Defining the P-value and 0.05 03:57 Statistical versus clinical significance 05:05 Sample size and the null hypothesis 08:07 How different is different? 10:49 The mistake everyone makes 13:38 Prior probability: seat belts versus astrology 16:05 A real study: Lipitor and kidney injury 17:26 Take-home points Learning objectives: After watching, you'll be able to: - Define the P-value and the null hypothesis in plain language - Distinguish statistical significance from clinical significance - Interpret a P-value in light of the prior probability that the finding is real 📺 Watch the full playlist on YouTube: https://www.youtube.com/playlist?list=PLh9mgdi4rNewVyTec_MVGxIbNSEeMhEsZ 🎓 Enroll on Coursera for assessments and a certificate: https://www.coursera.org/learn/medical-research 🌐 Explore more learning opportunities on Yale Online: https://online.yale.edu/courses/understanding-medical-research-your-facebook-friend-wrong