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Deborah Mayo | Statistics & Severe Testing vs Pseudoscience | Philosophy of Data Science

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#datascience #science #pseudoscience Deborah Mayo | Statistics & Severe Testing vs Pseudoscience | Philosophy of Data Science Watch it on… YouTube Podbean In our fourth episode of the “science vs pseudoscience” mini-series, Deborah Mayo (Virginia Tech) specifies several necessary criteria to be scientifically rigorous. She gives several examples of how statistical thinking is essential to scientific thinking and why she believes that the “I’ll know it when I see it” approach to delineating science from pseudoscience is not a good approach. Looking to catch up with the earlier “Science vs Pseudoscience” episode? You can watch them here: Intro : https://youtu.be/VB5C7ZNO8OY Episode 1: https://youtu.be/tDdEKxoop3Y Episode 2 : https://youtu.be/viz7u20cd5E Episode 3: https://youtu.be/zAjj45R8p2s 0:00 - Introduction 03:18 - Criteria of good science 12:05 - Circling back to Kuhn’s influence 21:50 - What is "normal science"? 25:10 - What would classify as revolutionary science? 28:50 - Introduction to discussing statistics and data science 39:30 - Defining what makes statistical methods good inquiry 47:28 - Defining pseudoscience and using the term 54:10 - Incentives in science

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