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Philosophy of Data Science | Deborah Mayo | Revolutions, Reforms, and Severe Testing in Statistical Thinking

Philosophy of Data Science | Deborah Mayo | Revolutions, Reforms, and Severe Testing in Statistical Thinking

FromData & Science with Glen Wright Colopy


Philosophy of Data Science | Deborah Mayo | Revolutions, Reforms, and Severe Testing in Statistical Thinking

FromData & Science with Glen Wright Colopy

ratings:
Length:
54 minutes
Released:
Feb 3, 2022
Format:
Podcast episode

Description

Philosophy of Data Science Series 
Keynote with Deborah Mayo
Episode 1: Revolutions, Reforms, and Severe Testing in Statistical Thinking
In the first keynote of the Philosophy of Data Science Series we have a 2-part interview with Deborah Mayo (Virginia Tech).
In the first part of our keynote with Deborah Mayo we cover...
- The role of scientific revolution and its implications for statistics and data scientist.
- The necessity of statistical reforms and why philosophy will play a role.
- The value of severe testing of scientific claims.

Watch it on... 
YouTube: https://youtu.be/S4VAEShM3BU
Podbean: 
You can join our mail list at: https://www.podofasclepius.com/mail-list
We're always happy to hear your feedback and ideas - just post it in the YouTube comment section to start a conversation. 
Thank you for your time and support of the series! 
 
Topics:
0:00 - Preface to First Keynote Interview
2:00 - Welcome Deborah Mayo!
5:05 - What is the Philosophy of Statistics?
8:15 - What does philosophy add to data science?
16:10 - Scientific revolution in statistics
20:10 - Statistical reforms
24:25 - Replication & hypothesis pre-specification
31:00 - Failure is severe testing
37:25 - Error statistics
48:00 - Scientific progress and closing remarks
Released:
Feb 3, 2022
Format:
Podcast episode

Titles in the series (88)

Data and Science with Glen Wright Colopy is a podcast covering critical scientific reasoning, particularly from a data science / machine learning / statistics perspective. Episodes typically focus on understanding of how to be better scientists and critical thinkers for the practical purpose of being a better data scientists. Previously called: ”Pod of Asclepius”