#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