Philosophy of Data Science | S02 E03 | Intro to Inductive Reasoning for Data Scientists

<p>Philosophy of Data Science Series  Session 2: Essential Reasoning Skills for Data Science Episode 3: Intro to Inductive Reasoning for Data Scientists</p> <p>Watch it on...  YouTube: https://youtu.be/lNOUvOUE_KE Podbean: https://podofasclepius.podbean.com/e/philosophy-of-data-science-s02-e03-intro-to-inductive-reasoning-for-data-scientists/</p> <p>New episodes of the Philosophy of Data Science Series will now be published on Mondays!</p> <p>Today's episode is a short introduction to a fundamental concept. Definitely worth your time!</p> <p>Inductive reasoning is the fundamental challenge to scientific rigor. Induction is baked into methods like K-fold cross validation or generalizing from a sample to a population. However, many statisticians and data scientists are unfamiliar with the term and its implications. Joseph Wu (Brown University) gets us up-to-speed with a 10-minute presentation on the fundamental role of induction in scientific reasoning.</p> <p>You can join our mail list at: https://www.podofasclepius.com/mail-list</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>Thank you for your time and support of the series! </p> <p>Outline 0:00 Intro 0:18 Inductive vs Deductive Reasoning 2:35 Overview of Induction, Deduction, and Abduction 3:23 Types of Induction: Everyday Life vs Statistical Generalizations 5:25 Sample to Population Induction 6:48 Population to Individual Induction 9:35 The Problem of Induction 11:52 Induction: Fallible but Powerful</p>