VARIABLES in Statistical Research (2-1)
A variable is any characteristic that can vary. An organized collection of numbers can be a variable. Qualitative variables indicate an attribute or belongingness to a category. Dichotomous variables are discrete variables that can have two and only two values. Quantitative variables indic
From playlist Forming Variables for Statistics & Statistical Software (WK 2 - QBA 237)
Intro to a Variable as a Changing Value or Placeholder
This video defines a variable and provides examples of a variable used as a changing value or a placeholder http://mathispower4u.com
From playlist Algebraic Structures Module
Linear regression (5): Bias and variance
Inductive bias; variance; relationship to over- & under-fitting
From playlist cs273a
Independent-samples T-tests 1: Introduction
In this video, I demonstrate how to calculate an independent-samples t-test and interpret the results.
From playlist Independent Samples t-Test
Statistic vs Parameter & Population vs Sample
This stats video tutorial explains the difference between a statistic and a parameter. It also discusses the difference between the population and sample. It includes examples such as the sample mean, population mean, sample standard deviation, population standard deviation, sample propo
From playlist Statistics
Using Variables in Science – The Foundations of Statistical Analysis and Scientific Testing (1-5)
Continuing our discussion about variables, you will learn how variables are used in science. Specifically, when we do statistics, we need independent and dependent variables. Independent variables are often categorical (groups) and dependent variables are typically measured on a scale. You
From playlist WK1 Numbers and Variables - Online Statistics for the Flipped Classroom
Fixed Effects and Random Effects
Brief overview in plain English of the differences between the types of effects. Problems with each model and how to overcome them.
From playlist Experimental Design
7. Ch. 3, Sections 3.1 & 3.2. Introduction to Logic, Philosophy 10, UC San Diego - BSLIF
Video lecture corresponding to _Basic Sentential Logic and Informal Fallacies_, Chapter 3, Sections 3.1 & 3.2. 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
Stanford Seminar - ML Explainability Part 2 I Inherently Interpretable Models
Professor Hima Lakkaraju presents some of the latest advancements in machine learning models that are inherently interpretable such as rule-based models, risk scores, generalized additive models and prototype based models. View the full playlist: https://www.youtube.com/playlist?list=PLoR
From playlist Stanford Seminars
What are Continuous Random Variables? (1 of 3: Relation to discrete data)
More resources available at www.misterwootube.com
From playlist Random Variables
3. Ch. 1 (Part 3/3). Introduction to Logic, Philosophy 10, UC San Diego - BSLIF
Video lecture corresponding to _Basic Sentential Logic and Informal Fallacies_, Chapter 1, Part 3 of 3. 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
2. Ch. 1 (Part 2/3). Introduction to Logic, Philosophy 10, UC San Diego - BSLIF
Video lecture corresponding to _Basic Sentential Logic and Informal Fallacies_, Chapter 1, Part 2 of 3. 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
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Mark Seifter In this mega-recitation, we cover Problem 1 from Quiz 1, Fall 2009. We begin with the rules and assertions, then spend most of our time on backward chaining and dra
From playlist MIT 6.034 Artificial Intelligence, Fall 2010
Lecture 15: Coreference Resolution
Lecture 15 covers what is coreference via a working example. Also includes research highlight "Summarizing Source Code", an introduction to coreference resolution and neural coreference resolution. ------------------------------------------------------------------------------- Natural La
From playlist Lecture Collection | Natural Language Processing with Deep Learning (Winter 2017)
Stepan Kuznetsov: Relational models for the Lambek calculus with intersection and unit
HYBRID EVENT Recorded during the meeting "19th International Conference on Relational and Algebraic Methods in Computer Science" the November 5, 2021 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other t
From playlist Logic and Foundations
Undertale Propositional Logic (#SoME2)
I'm sorry I had to do it because of the memes. Crash course educational look of propositional logic with the motivation to show how to prove things through proof by contradiction and proof by contraposition. Honorable shoutouts to @blackpenredpen and @drpeyam. God bless Toby Fox! Timel
From playlist Summer of Math Exposition 2 videos
Prob & Stats - Random Variable & Prob Distribution (1 of 53) Random Variable
Visit http://ilectureonline.com for more math and science lectures! In this video I will define and gives an example of what is a random variable. Next video in series: http://youtu.be/aEB07VIIfKs
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution
Axel Osmond - The over-topos at a model
Talk at the school and conference “Toposes online” (24-30 June 2021): https://aroundtoposes.com/toposesonline/ Slides: https://aroundtoposes.com/wp-content/uploads/2021/07/OsmondSlidesToposesOnline.pdf For a model of a geometric theory in a Grothendieck topos, we can construct the over-t
From playlist Toposes online