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

<p>Philosophy of Data Science Series</p> <p>Session 2: Essential Reasoning Skills for Data Science</p> <p>Episode 1: Round Table on Essential Reasoning Skills for Data Science</p> <p> </p> <p>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).</p> <p> </p> <p>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.</p> <p> </p> <p>Watch it on...</p> <p>YouTube: <a href='https://www.youtube.com/watch?v=5bOuy6VA8Hg'>https://www.youtube.com/watch?v=5bOuy6VA8Hg </a></p> <p>Podbean: https://podofasclepius.podbean.com/e/philosophy-of-data-science-s02-e01-round-table-on-essential-reasoning-skills-for-data-science/</p> <p> </p> <p>You can join our mail list at: https://www.podofasclepius.com/mail-list</p> <p> </p> <p>We're always happy to hear your feedback and ideas - just post it in the YouTube comment section to start a conversation.</p> <p> </p> <p>Thank you for your time and support of the series!</p> <p> </p> <p>0:00 Intro</p> <p>0:10 Roundtable on Critical Reasoning Skills</p> <p>2:50 Guest Introductions</p> <p>5:48 Thesis: Data Science Use All Modes of Reasoning Daily</p> <p>6:45 Taxonomy of Deduction, Induction, and Abduction</p> <p>17:21 The Problem of Induction</p> <p>32:18 The Problem of Induction Creeping into Deduction</p> <p>36:45 Bayesian Applicability Indices and Signal Quality Indices</p> <p>40:55 What is "The" Scientific Method?</p> <p>44:08 What is Pseudo-Science?</p> <p>47:35 Theory vs Data/Evidence</p> <p>50:48