Diagonalization is the process of re-ordering the rows and columns of tables and charts so that the data forms an approximately diagonal line. This makes it easier for people to see patterns in the data. Diagonalization typically involves either raw data, percentages, means or residuals. Generally once tables are diagonalized one of two patterns appears: hierarchy or segmentation (Wikipedia).
The Diagonalization of Matrices
This video explains the process of diagonalization of a matrix.
From playlist The Diagonalization of Matrices
Characterizations of Diagonalizability In this video, I define the notion of diagonalizability and show what it has to do with eigenvectors. Check out my Diagonalization playlist: https://www.youtube.com/playlist?list=PLJb1qAQIrmmCSovHY6cXzPMNSuWOwd9wB Subscribe to my channel: https://
From playlist Diagonalization
This video defines a diagonal matrix and then explains how to determine the inverse of a diagonal matrix (if possible) and how to raise a diagonal matrix to a power. Site: mathispower4u.com Blog: mathispower4u.wordpress.com
From playlist Introduction to Matrices and Matrix Operations
How the Diagonalization Process Works
Description: Our goal is to fix a diagonal matrix that is similar to our given matrix. Why? Diagonal matrices are simple, and if two matrices are similar then they share many properties like the same eigenvalues. So similar to a diagonal matrix will allows us to quickly compute many proper
From playlist Linear Algebra (Full Course)
Determine the Product of a Matrix and Vector using the Diagonalization of the Matrix
This video explains how to use the diagonalization of a 2 by 2 matrix to find the product of a matrix and a vector given matrix P and D.
From playlist The Diagonalization of Matrices
In this video, I define the notion of simultaneous diagonalization and show that two matrices are simultaneously diagonalizable if and only if they commute (that is AB = BA). This is a wonderful exercise using invariant subspaces and diagonalization. Enjoy! Check out my Diagonalization pl
From playlist Diagonalization
We have already looked at the column view of a matrix. In this video lecture I want to expand on this topic to show you that each matrix has a column space. If a matrix is part of a linear system then a linear combination of the columns creates a column space. The vector created by the
From playlist Introducing linear algebra
Now that we know about eigenvalues and eigenvectors, we are ready to learn about diagonalization. This involves writing a matrix as a product of other matrices, one of which is a diagonal matrix, with values only along the main diagonal. This has many applications in computation, so let's
From playlist Mathematics (All Of It)
Is the Sieve of Eratosthenese past its prime?
The Sieve of Eratosthenes is an amazing tool for teaching people about prime numbers and composite numbers but it's not without its limitations. I've tried to answer the question, 'Is there a better way of representing a sieve like this?' 0:00 Sieve of Eratosthenes In the first part of t
From playlist Summer of Math Exposition Youtube Videos
This is lecture 3 of an online mathematics course on group theory. It gives a review of homomorphisms and isomorphisms and gives some examples of these.
From playlist Group theory
THE BASICS: Horizontal-Vertical-Diagonal Alignment-Your drawing's scaffolding
Marc discusses and demonstrates the often hidden mental aligning techniques artists use to control a perceptual drawing-Horizontal-Vertical-Diagonal Alignment.
From playlist THE BASICS
JASP 0.10 Tutorial: Correlations (Episode 9)
In this JASP tutorial, I go through a Correlation Matrix example, discussing and explaining each option you can use to fully explore the test. The data presented here is mine and is unpublished. I am using it for demonstration purposes only. Proper credit should be given if used elsewhere
From playlist JASP Tutorials
Ichess 5: K + r, N + r, and Mex
In the fifth video in the Impartial Chess series, we explore the games of King + Baby Rook, Knight + Baby Rook, and discuss the concept of the minimal excludant. To see how we found the Knight's Grundy Table at 6:33, watch Ichess 5 1/2: https://www.youtube.com/watch?v=X3M7vhh2T_g&list=PLj
From playlist Intro to Impartial Combinatorial Games and Their Theory
Unified Charge Vectors (UCV Theory) by Noam Why. Grand unification of electroweak and strong forces.
A new breakthrough in theoretical physics! UCV theory is a grand unification of electroweak and strong forces based on a new idea called Unified Charge Vectors. The theory was developed by Noam Why and was first published in January 2021. Original paper: https://independent.academia.edu/W
From playlist Summer of Math Exposition Youtube Videos
Chemistry 107. Inorganic Chemistry. Lecture 04
UCI Chemistry: Inorganic Chemistry (Fall 2014) Lec 04. Inorganic Chemistry -- Character Tables and One Application of Symmetry View the complete course: http://ocw.uci.edu/courses/chem_107_inorganic_chemistry.html Instructor: Matthew D. Law License: Creative Commons CC-BY-SA Terms of Use:
From playlist Chem 107: Week 2
Ichess 5 and 1/2: N and His Grundy Table
This video serves as a more in-depth explanation of the Knight's Grundy Table seen in Ichess 5.
From playlist Intro to Impartial Combinatorial Games and Their Theory
The Unknown Secrets of Times Table.
You don’t need to learn hard staff in mathematics to appreciate its beauty ! We understand the tricks hiding inside times table- something all of us seem to understand ! Patreon: https://www.patreon.com/MetaMaths Source code for Manim animations: https://github.com/univalency/Manim-anima
From playlist Something you did not know...
A double feature on magic squares featuring Bachet's algorithm embedded in the Korean historical drama series Tree with deep roots and the Lee Sallow's geomagic squares. 00:00 Intro 02:52 Part 1: The king's magic squares 09:40 Proof 18:22 The order 5 and 7 magic squares 19:17 Part 2: Geom
From playlist Recent videos
Linear Algebra - Lecture 35 - Diagonalizable Matrices
In this lecture, we discuss what it means for a square matrix to be diagonalizable. We prove the Diagonalization Theorem, which tells us exactly when a matrix is diagonalizable.
From playlist Linear Algebra Lectures