Theorems in propositional logic | Rules of inference
In propositional logic, tautology is either of two commonly used rules of replacement. The rules are used to eliminate redundancy in disjunctions and conjunctions when they occur in logical proofs. They are: The principle of idempotency of disjunction: and the principle of idempotency of conjunction: Where "" is a metalogical symbol representing "can be replaced in a logical proof with." (Wikipedia).
Basic Methods: We define tautology and contradiction and consider the conditions of logical equivalence and implication. Examples include DeMorgan's Laws for logic, modus ponens, and the Law of the Excluded Middle. As a final note, we introduce the Substitution Rules.
From playlist Math Major Basics
Discrete Math - 1.6.1 Rules of Inference for Propositional Logic
Building a valid argument using rules of inference for propositions. Textbook: Rosen, Discrete Mathematics and Its Applications, 7e Playlist: https://www.youtube.com/playlist?list=PLl-gb0E4MII28GykmtuBXNUNoej-vY5Rz
From playlist Discrete Math I (Entire Course)
RULES of INFERENCE - DISCRETE MATHEMATICS
We talk about rules of inference and what makes a valid argument. We discuss modus ponens, modus tollens, hypothetical syllogism, disjunctive syllogism, addition, simplification, and conjunction. #DiscreteMath #Mathematics #Logic #RulesOfInference LIKE AND SHARE THE VIDEO IF IT HELPED!
From playlist Discrete Math 1
Causal Inference is a set of tools used to scientifically prove cause and effect, very commonly used in economics and medicine. This series will go over the basics that any data scientist should understand about causal inference - and point them to the tools they would need to perform it.
From playlist Causal Inference - The Science of Cause and Effect
Inference Rules via the Algebra of Boole | MathFoundations 275 | N J Wildberger
We show how to introduce Inference Rules in Propositional Logic in the framework of the Algebra of Boole, which provides a cut and dried technology to easily establish all such rules. Prominent amongst these are Modus Ponens, Modus Tollens, Hypothetical Syllogism and Disjunctive Syllogism
From playlist Boole's Logic and Circuit Analysis
12. Ch. 4, Section 4.7. Introduction to Logic, Philosophy 10, UC San Diego - BSLIF
Video lecture corresponding to _Basic Sentential Logic and Informal Fallacies_, Chapter 4, Section 4.7. This is for the class Introduction to Logic, Philosophy 10, UC San Diego.
From playlist UC San Diego: PHIL 10 - Introduction to Logic | CosmoLearning.org Philosophy
Logical Arguments, Formal Implication, and Laws of Inference [Discrete Math Class]
This video is not like my normal uploads. This is a supplemental video from one of my courses that I made in case students had to quarantine. this is a follow up to previous videos introducing propositional logic (mathematical propositions; logical connectives - "and", "or", "not" , the co
From playlist Discrete Mathematics Course
Ideal Experiment - Causal Inference
In this video, I give you more details about the fundamental question and the fundamental problem of causal inference with the help of an example (our ideal experiment).
From playlist Causal Inference - The Science of Cause and Effect
Wittgenstein on Rules & Private Language
Something from the other channel that I made awhile back. The audio is from: https://www.youtube.com/watch?v=g2JVMOkoDo8 Some relevant quotes: "But how can a rule show me what I have to do at this point? Whatever I do is, on some interpretation, in accord with the rule...Any interpretati
From playlist Wittgenstein
This video functions as a brief introduction to many different topics in formal logic. Notes on the Images: I looked into the legality of using images for this video a good deal and I've come to the conclusion that there is nothing in this video which could remotely imply these images ar
From playlist Summer of Math Exposition 2 videos
The Ultimate Guide to Propositional Logic for Discrete Mathematics
This is the ultimate guide to propositional logic in discrete mathematics. We cover propositions, truth tables, connectives, syntax, semantics, logical equivalence, translating english to logic, and even logic inferences and logical deductions. 00:00 Propositions 02:47 Connectives 05:13 W
From playlist Discrete Math 1
Short proofs are hard to find (joint work w/ Toni Pitassi and Hao Wei) - Ian Mertz
Computer Science/Discrete Mathematics Seminar II Topic: Short proofs are hard to find (joint work w/ Toni Pitassi and Hao Wei) Speaker: Ian Mertz Affiliation: University of Toronto Date: December 5, 2017 For more videos, please visit http://video.ias.edu
From playlist Mathematics
Model Theory - part 06 - Quantifiers as Adjoints
In this video we start to talk about how one can view quantifiers as adjoints of certain functors.
From playlist Model Theory
We describe my favorite causal inference technique: the parametric G formula, my go-to for any standard observational causal inference problems
From playlist Causal Inference - The Science of Cause and Effect
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
VALID arguments, SOUND arguments, and ENTAILMENT - Logic
In this video on #Logic / #PhilosophicalLogic we look at valid arguments, sound arguments, and learn how to determine validity using truth tables. We do a few examples. 0:00 [Intro] 0:13 [Valid Arguments] 1:16 [Sound Arguments] 2:30 [Valid Arguments and Truth Tables] 06:08 [Example Questi
From playlist Logic in Philosophy and Mathematics
6 - Bayes' rule in inference - likelihood
Provides an introduction to Bayesian statistics - in particular the likelihood - by running through a simple example of the application of Bayes' rule to the case of inference over a binary parameter, If you are interested in seeing more of the material, arranged into a playlist, please v
From playlist Bayesian statistics: a comprehensive course
Efficient reasoning in PAC semantics - Brendan Juba
Brendan Juba Harvard University November 18, 2013 Machine learning is often employed as one step in a larger application, serving to perform information extraction or data mining for example. The rules obtained by such learning are then used as inputs to a further analysis. As a consequenc
From playlist Mathematics