What are Residuals in Regression?
Brief intro to residuals in regression. What they are and what they look like in relation to a line of best fit. Sum and mean of residuals.
From playlist Regression Analysis
Least squares method for simple linear regression
In this video I show you how to derive the equations for the coefficients of the simple linear regression line. The least squares method for the simple linear regression line, requires the calculation of the intercept and the slope, commonly written as beta-sub-zero and beta-sub-one. Deriv
From playlist Machine learning
Using residuals to analyze the data
From playlist Unit 3: Linear and Non-Linear Regression
Standard deviation of residuals or Root-mean-square error (RMSD)
Calculating the standard deviation of residuals (or root-mean-square error (RMSD) or root-mean-square deviation (RMSD)) to measure disagreement between a linear regression model and a set of data.
From playlist Exploring bivariate numerical data | AP Statistics | Khan Academy
EstimatingRegressionCoeff.6.MinimizingSums
This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources
From playlist Estimating Regression Coefficients
Labeling a System by Solving Using Elimination Method
👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e
From playlist Solve a System of Equations Using Elimination | Medium
Transformation and Weighting to correct model inadequacies (Part C)
Regression Analysis by Dr. Soumen Maity,Department of Mathematics,IIT Kharagpur.For more details on NPTEL visit http://nptel.ac.in
From playlist IIT Kharagpur: Regression Analysis | CosmoLearning.org Mathematics
DDPS | Towards reliable, efficient, and automated model reduction of parametrized nonlinear PDEs
Description: Many engineering tasks, such as parametric study and uncertainty quantification, require rapid and reliable solution of partial differential equations (PDEs) for many different configurations. In this talk, we consider goal-oriented model reduction of parametrized nonlinear PD
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Welch's Method: The Averaged Periodogram
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Poor variance properties of the periodogram motivate averaging methods for estimating the power spectrum. In Welch's method the data is partit
From playlist Estimation and Detection Theory
12b Geostatistics Course: Kriging
Lecture on kriging for spatial estimation.
From playlist Data Analytics and Geostatistics
Geostatistics session 3 universal kriging
Introduction to Universal Kriging
From playlist Geostatistics GS240
Ana Caraiani - Modularity over CM fields
I will discuss joint work in progress with James Newton, where we prove a local-global compatibility result in the crystalline case for Galois representations attached to torsion classes occurring in the cohomology of locally symmetric spaces. I will then explain an application to the modu
From playlist Franco-Asian Summer School on Arithmetic Geometry (CIRM)
Modularity lifting theorems for non-regular symplectic representations - George Boxer
Workshop on Motives, Galois Representations and Cohomology Around the Langlands Program Topic: Modularity lifting theorems for non-regular symplectic representations Speaker: George Boxer Affiliation: University of Chicago Date: November 7, 2017 For more videos, please visit http://vide
From playlist Mathematics
Potential Automorphy for Compatible Systems of l-Adic Galois Representations - David Geraghty
David Geraghty Princeton University; Member, School of Mathematics November 18, 2010 I will describe a joint work with Barnet-Lamb, Gee and Taylor where we establish a potential automorphy result for compatible systems of Galois representations over totally real and CM fields. This is ded
From playlist Mathematics
Ensembles (3): Gradient Boosting
Gradient boosting ensemble technique for regression
From playlist cs273a
János Pintz: Large values of the remainder term of the prime number theorem
CIRM VIRTUAL CONFERENCE Recorded during the meeting "​ Diophantine Problems, Determinism and Randomness" the November 26, 2020 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide
From playlist Virtual Conference
STAT 200 Lesson 3 Full Video Lecture
Describing Data Part 2 Table of Contents: 00:34 - 1. Construct and interpret a boxplot and side-by-side boxplots 03:58 - Minitab Express: Boxplot & side-by-side boxplots 06:24 - 2. Use the IQR method to identify outliers 11:46 - 3. Construct and interpret histograms with group
From playlist STAT 200 Video Lectures
EstimatingRegressionCoeff.5.Residuals
This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources
From playlist Estimating Regression Coefficients