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Philosophy of Data Science | S02 E01 | Round Table on Essential Reasoning Skills for Data Science

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Philosophy of Data Science Series

Session 2: Essential Reasoning Skills for Data Science

Episode 1: Round Table on Essential Reasoning Skills for Data Science

 

Session 2 "Essential Reasoning Skills for Data Scientists" is kicking off with a roundtable discussion with Elina Vessonen (Finnish Institute for Health & Welfare), Joseph Wu (Brown University), and Huub Brouwer (Tilburg University & Utrecht University).

 

One of the major challenges in data science is that we use three different modes of critical reasoning (deduction, induction, and abduction) on a daily (or even hourly) basis. It's important to understand the strengths and weaknesses of each mode of reasoning so that we can apply them as appropriate. This round table will begin this conversation on the modes of reasoning and how it applies to & science and data science.

 

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YouTube: https://www.youtube.com/watch?v=5bOuy6VA8Hg

Podbean: https://podofasclepius.podbean.com/e/philosophy-of-data-science-s02-e01-round-table-on-essential-reasoning-skills-for-data-science/

 

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!

 

0:00 Intro

0:10 Roundtable on Critical Reasoning Skills

2:50 Guest Introductions

5:48 Thesis: Data Science Use All Modes of Reasoning Daily

6:45 Taxonomy of Deduction, Induction, and Abduction

17:21 The Problem of Induction

32:18 The Problem of Induction Creeping into Deduction

36:45 Bayesian Applicability Indices and Signal Quality Indices

40:55 What is "The" Scientific Method?

44:08 What is Pseudo-Science?

47:35 Theory vs Data/Evidence

50:48 Final Remarks

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Philosophy of Data Science | S02 E01 | Round Table on Essential Reasoning Skills for Data Science

Data & Science with Glen Wright Colopy

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