In statistics, canonical-correlation analysis (CCA), also called canonical variates analysis, is a way of inferring information from cross-covariance matrices. If we have two vectors X = (X1, ..., Xn) and Y = (Y1, ..., Ym) of random variables, and there are correlations among the variables, then canonical-correlation analysis will find linear combinations of X and Y which have maximum correlation with each other. T. R. Knapp notes that "virtually all of the commonly encountered parametric tests of significance can be treated as special cases of canonical-correlation analysis, which is the general procedure for investigating the relationships between two sets of variables." The method was first introduced by Harold Hotelling in 1936, although in the context of angles between flats the mathematical concept was published by Jordan in 1875. (Wikipedia).
Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2015 This video covers how to run a canonical correlation in SPSS using the syntax provided on IBM's website, along with data screening. Lecture materials and assignments available at statisticsofdoom.com. https://statisti
From playlist Advanced Statistics Videos
Conceptual Questions about Correlation
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Conceptual Questions about Correlation
From playlist Statistics
Fan Yang (U Penn) -- Sample canonical correlation coefficients of high-dimensional random vectors
We study the the sample correlation between two ensembles of high dimensional random vectors from the perspective of canonical-correlation analysis (CCA). Assuming almost sharp moment assumptions on the vector entries, we prove that the finite rank correlations will lead to outliers in the
From playlist Northeastern Probability Seminar 2020
This video explains how to find the correlation coefficient which describes the strength of the linear relationship between two variables x and y. My Website: https://www.video-tutor.net Patreon: https://www.patreon.com/MathScienceTutor Amazon Store: https://www.amazon.com/shop/theorga
From playlist Statistics
Correlation does not Imply Causality, but then again… (7-4)
Correlation Does Not Imply Causation. When we see a correlation, we should not assume a cause-and-effect relationship between the variables. Correlation does not mean one isn’t causing the other, either; we just need more information. The correlation between two variables may be caused by
From playlist Correlation And Regression in Statistics (WK 07 - QBA 237)
RELATIONSHIPS Between Variables: Standardized Covariance (7-1)
Correlation is a way of measuring the extent to which two variables are related. The term correlation is synonymous with “relationship.” Variables are related when changes in one variable are consistently associated with changes in another variable. Dr. Daniel reviews Variance, Covariance,
From playlist Correlation And Regression in Statistics (WK 07 - QBA 237)
Intro to the Correlation Coefficient
Brief intro to the correlation coefficient. What it means to have negative correlation, positive correlation or zero correlation. Pearson's, sample and population formulas.
From playlist Correlation
Foundational Correlation – The Correlation Coefficient (13-5)
The correlational coefficient measures how closely the data fit the model of a straight line on a scatterplot diagram. The concept of correlation was invented by Sir Frances Galton and developed by statistician Karl Pearson. Linear correlation means that the correlation can be graphed in a
From playlist WK13 Correlation - Online Statistics for the Flipped Classroom
Victor Panaretos: The extrapolation of correlation
CONFERENCE Recording during the thematic meeting : "Adaptive and High-Dimensional Spatio-Temporal Methods for Forecasting " the September 29, 2022 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks
From playlist Analysis and its Applications
Inspecting Neural Networks with CCA - A Gentle Intro (Explainable AI for Deep Learning)
Canonical Correlation Analysis is one of the methods used to explore deep neural networks. Methods like CKA and SVCCA reveal to us insights into how a neural network processes its inputs. This is often done by using CKA and SVCCA as a similarity measure for different activation matrices. I
From playlist Explainable AI Guide
Introduction to direct forecasting to solve UQ problems
From playlist QUSS GS 260
Charge-current correlation equalities far from thermal equilibrium by Gunter Schutz
PROGRAM THERMALIZATION, MANY BODY LOCALIZATION AND HYDRODYNAMICS ORGANIZERS: Dmitry Abanin, Abhishek Dhar, François Huveneers, Takahiro Sagawa, Keiji Saito, Herbert Spohn and Hal Tasaki DATE : 11 November 2019 to 29 November 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore How do is
From playlist Thermalization, Many Body Localization And Hydrodynamics 2019
An Introduction to Gauge/gravity Duality and Holographic Renorma... (Lecture 3) by Kostas Skenderis
PROGRAM NONPERTURBATIVE AND NUMERICAL APPROACHES TO QUANTUM GRAVITY, STRING THEORY AND HOLOGRAPHY (HYBRID) ORGANIZERS: David Berenstein (University of California, Santa Barbara, USA), Simon Catterall (Syracuse University, USA), Masanori Hanada (University of Surrey, UK), Anosh Joseph (II
From playlist NUMSTRING 2022
Session 1 - A State Dependent Description of the Black Hole Interior: Suvrat Raju
https://strings2015.icts.res.in/talkTitles.php
From playlist Strings 2015 conference
Out of equilibrium dynamics of complex systems by Leticia Cugliandolo
PROGRAM : BANGALORE SCHOOL ON STATISTICAL PHYSICS - XII (ONLINE) ORGANIZERS : Abhishek Dhar (ICTS-TIFR, Bengaluru) and Sanjib Sabhapandit (RRI, Bengaluru) DATE : 28 June 2021 to 09 July 2021 VENUE : Online Due to the ongoing COVID-19 pandemic, the school will be conducted through online
From playlist Bangalore School on Statistical Physics - XII (ONLINE) 2021
Motivic correlators and locally symmetric spaces IV - Alexander Goncharov
Locally Symmetric Spaces Seminar Topic: Motivic correlators and locally symmetric spaces IV Speaker: Alexander Goncharov Affiliation: Yale University; Member, School of Mathematics and Natural Sciences Date: December 5, 2017 For more videos, please visit http://video.ias.edu
From playlist Mathematics
Four Uses of Correlation in Statistics (13-3)
Correlation is fundamentally about understanding the direction and strength of the relationship between variables, but it can also do a number of other useful jobs. • Correlation can test for reliability, such as test-retest reliability or Cronbach’s alpha. • Correlation can test for val
From playlist WK13 Correlation - Online Statistics for the Flipped Classroom