Choosing a Statistical Test | Understanding Medical Research

Choosing a statistical test comes down to two facts: what type of data the exposure is and what type the outcome is. This video covers the chart that maps data types to tests, with the chi-square test, Student's t-test, and Pearson correlation as worked examples. Chapters: 00:00 Goals and the right tool for the job 01:43 Is 175 different from 180? 02:49 Why medicine is not coin flips 03:26 Exposure type, outcome type, and the master chart 05:53 Chi-square: a progeria drug trial 07:32 Student's t-test: flibanserin 09:22 Correlation: empathy and politics by specialty 10:40 Take-home points Learning objectives: After watching, you'll be able to: - Explain what researchers mean when they say two results are or are not "different" - Identify the two pieces of information needed to choose a statistical test - Recognize when a chi-square test, Student's t-test, or Pearson correlation fits the data 📺 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