Mathematics and Plausible Reasoning is a two-volume book by the mathematician George Pólya describing various methods for being a good guesser of new mathematical results. In the Preface to Volume 1 of the book Pólya exhorts all interested students of mathematics thus: "Certainly, let us learn proving, but also let us learn guessing." P. R. Halmos reviewing the book summarised the central thesis of the book thus: ". . . a good guess is as important as a good proof." (Wikipedia).
Logic: The Structure of Reason
As a tool for characterizing rational thought, logic cuts across many philosophical disciplines and lies at the core of mathematics and computer science. Drawing on Aristotle’s Organon, Russell’s Principia Mathematica, and other central works, this program tracks the evolution of logic, be
From playlist Logic & Philosophy of Mathematics
SImple proofs and their variations -- Proofs
This lecture is on Introduction to Higher Mathematics (Proofs). For more see http://calculus123.com.
From playlist Proofs
Basic Methods: We define theorems and describe how to formally construct a proof. We note further rules of inference and show how the logical equivalence of reductio ad absurdum allows proof by contradiction.
From playlist Math Major Basics
Logical Reasoning: Become A Better Thinker
Logical thinking is also known as analytical reasoning, critical thinking or abstract thinking. It is an important trait, especially among developers in the software development industry. Without the logic, they would not understand how the software works, nor would they produce a clean co
From playlist Problem Solving
An introduction to the general types of logic statements
From playlist Geometry
Ch. 8 - Logic - Valid Arguments (IB Math Studies)
Hello and welcome to What Da Math This video is an explanation of the following terms from logic, chapter 8: Valid arguments and truth tables using implications and conjunctions SUBSCRIBE for more math and math studies videos Join me on Twitter: http://twitter.com/WhatDaMath
From playlist IB Math Studies Chapter 8
Teach Astronomy - Scientific Reasoning
http://www.teachastronomy.com/ Scientific reasoning is an important part of how science works. You may have your own beliefs or your own faith, and they are your own. They're unchallengeable. But if you make an assertion in a scientific way, you have to be able to back up that assertion
From playlist 01. Fundamentals of Science and Astronomy
The logic of AND/OR and intersections/unions -- Introduction to Higher Mathematics
This lecture is on Introduction to Higher Mathematics. For more see http://calculus123.com.
From playlist Proofs
This video focuses on how to write the converse of a conditional statement. In particular, this video shows how to flip the hypothesis and conclusion of a conditional statement. The concepts of truth value and logical equivalence are explored as well. Your feedback and requests are encour
From playlist Geometry
Statistical Rethinking 2022 Lecture 02 - Bayesian Inference
Bayesian updating, sampling posterior distributions, computing posterior and prior predictive distributions Course materials: https://github.com/rmcelreath/stat_rethinking_2022 Intro music: https://www.youtube.com/watch?v=QH_VKWStK98 Chapters: 00:00 Introduction 04:53 Garden of forking
From playlist Statistical Rethinking 2022
Scientific Method | Introductory Astronomy Course 1.08
Welcome to Astronomy: Exploring Time and Space, a course from Professor Impey, a University Distinguished Professor of Astronomy at the University of Arizona. Learn about the foundations of astronomy in this free online course here on YouTube. This video is part of module 1, Science and Hi
From playlist Introductory Astronomy Module 1: Science and History
The Future of Crime Detection and Prevention
Could an artificial intelligence predict a crime before it happens? Will we ever truly trust a machine? What new technology might be used against us in the future? Subscribe for regular science videos: http://bit.ly/RiSubscRibe Our expert panel will open our eyes and try to allay our fear
From playlist Ri Talks
Protecting Privacy with MATH (Collab with the Census)
This video was made in collaboration with the US Census Bureau and fact-checked by Census Bureau scientists. Any opinions and errors are my own. For more information, visit https://census.gov/about/policies/privacy/statistical_safeguards.html or search "differential privacy" at http://cens
From playlist MinutePhysics
In this lecture, Dr Arif Ahmed (University of Cambridge) thinks about the concept of knowledge and the analysis of a particular category of knowledge called ‘propositional knowledge’ (also known as ‘knowledge that’). In particular, we focus on: (i) the distinction between different kinds o
From playlist Philosophy
Q&A The Big Picture - with Sean Carroll
Does religion carry any scientific relevance? How did the universe become asymmetrical? Will we be able to overcome death? Sean Carroll addresses audience questions after his lecture. Subscribe for regular science videos: http://bit.ly/RiSubscRibe Dr Sean Carroll is an astrophysicist at t
From playlist Ri Talks
Statistical Rethinking 2022 Lecture 03 - Geocentric Models
Linear regression from a Bayesian perspective Slides and course materials: https://github.com/rmcelreath/stat_rethinking_2022 Music Intro: https://www.youtube.com/watch?v=4y33h81phKU Flow: https://www.youtube.com/watch?v=ip4n8zaTg1w Pause: https://www.youtube.com/watch?v=1f-NQAgm-YM Cha
From playlist Statistical Rethinking 2022
Mini-course on information by Rajaram Nityananda (Part 1)
Information processing in biological systems URL: https://www.icts.res.in/discussion_meeting/ipbs2016/ DATES: Monday 04 Jan, 2016 - Thursday 07 Jan, 2016 VENUE: ICTS campus, Bangalore From the level of networks of genes and proteins to the embryonic and neural levels, information at var
From playlist Information processing in biological systems
Statistical Rethinking Winter 2019 Lecture 02
Lecture 02 of the Dec 2018 through March 2019 edition of Statistical Rethinking: A Bayesian Course with R and Stan. This lectures covers the material in Chapters 2 and 3 of the book.
From playlist Statistical Rethinking Winter 2019
Peter Bühlmann : The power of heterogeneous large-scale data for high-dimensional causal inference
Abstract: We present a novel methodology for causal inference based on an invariance principle. It exploits the advantage of heterogeneity in larger datasets, arising from different experimental conditions (i.e. an aspect of "Big Data"). Despite fundamental identifiability issues, the meth
From playlist Probability and Statistics
The problem with `functions' | Arithmetic and Geometry Math Foundations 42a
[First of two parts] Here we address a core logical problem with modern mathematics--the usual definition of a `function' does not contain precise enough bounds on the nature of the rules or procedures (or computer programs) allowed. Here we discuss the difficulty in the context of funct
From playlist Math Foundations