Linear regression is used to compare sets or pairs of numerical data points. We use it to find a correlation between variables.
From playlist Learning medical statistics with python and Jupyter notebooks
Linear Regression using Python
This seminar series looks at four important linear models (linear regression, analysis of variance, analysis of covariance, and logistic regression). A video that explains all four model types is at https://www.youtube.com/watch?v=SV9AxXFWZnM&t=12s This video is on linear regression usin
From playlist Statistics
More Standard Deviation and Variance
Further explanations and examples of standard deviation and variance
From playlist Unit 1: Descriptive Statistics
Statistical Modeling in Business Analytics with R | Edureka
( R Training : https://www.edureka.co/r-for-analytics ) A statistical model is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more other variables. The topics in
From playlist R Tutorial Videos
Statistical Modeling in Business Analytics with R | Edureka
( R Training : https://www.edureka.co/r-for-analytics ) A statistical model is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more other variables. The topic co
From playlist R Tutorial Videos
Linear regression ANOVA ANCOVA Logistic Regression
In this video tutorial you will learn about the fundamentals of linear modeling: linear regression, analysis of variance, analysis of covariance, and logistic regression. I work through the results of these tests on the white board, so no code and no complicated equations. Linear regressi
From playlist Statistics
Introduces notation and formulas for exponential growth models, with solutions to guided problems.
From playlist Discrete Math
(ML 16.7) EM for the Gaussian mixture model (part 1)
Applying EM (Expectation-Maximization) to estimate the parameters of a Gaussian mixture model. Here we use the alternate formulation presented for (unconstrained) exponential families.
From playlist Machine Learning
1a Data Analytics Reboot: Statistics Concepts
Lecture on basic statistical / data analytics concepts with a bias toward spatial and subsurface applications. Data Analytics and Geostatistics is an undergraduate course that I teach fall and spring semesters at The University of Texas at Austin. We build up fundamental spatial, subsurfa
From playlist Data Analytics and Geostatistics
Statistical Rethinking 2022 Lecture 01 - Golem of Prague
Introduction to the course: Goals, golems, drawing the owl, meet a DAG Slides available on course webpage: https://github.com/rmcelreath/stat_rethinking_2022 Intro music: https://www.youtube.com/watch?v=S61ENc51Z1Q Prague music: https://www.youtube.com/watch?v=vO6x49wBKi8 Chapters: 00:00
From playlist Statistical Rethinking 2022
Statistical Rethinking 2023 - 01 - The Golem of Prague
Full course details at https://github.com/rmcelreath/stat_rethinking_2023 Chapters: 00:00 Introduction 03:30 DAGs (causal models) 17:50 Golems (stat models) 43:06 Owls (workflow) Intro music: https://www.youtube.com/watch?v=9yHZdLswArc
From playlist Statistical Rethinking 2023
Selecting the BEST Regression Model (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
Engineering CEE 20: Engineering Problem Solving. Lecture 16
UCI CIvil & Environmental Engineering 20 Engineering Problem Solving (Spring 2013) Lec 16. Engineering Problem Solving View the complete course: http://ocw.uci.edu/courses/cee_20_introduction_to_computational_engineering_problem_solving.html Instructor: Jasper Alexander Vrugt, Ph.D. Lice
From playlist Engineering CEE 20: Engineering Problem Solving
Agnès Desolneux - Maximum Entropy Distributions for Image Synthesis under Statistical Constraints
The question of texture synthesis in image processing is a very challenging problem that can be stated as followed: given an exemplar image, sample a new image that has the same statistical features (empirical mean, empirical covariance, filter responses, neural network responses, etc.). E
From playlist Journée statistique & informatique pour la science des données à Paris-Saclay 2021
Statistical Rethinking 2022 Lecture 20 - Horoscopes
Slides and other course materials: https://github.com/rmcelreath/stat_rethinking_2022 Music: https://www.youtube.com/watch?v=g2GbpXqL5P8 Pause: https://www.youtube.com/watch?v=pxPdsqrQByM Chapters: 00:00 Introduction 08:26 Subjective responsibilities 14:36 Planning 34:34 Working 58:28 Re
From playlist Statistical Rethinking 2022
Fellow Short Talks: Professor David Firth, University of Warwick
Bio Professor of Statistics at Warwick and Director of WDSI. Previously Professor of Social Statistics at Oxford. ESRC Professorial Fellow (2003-2006). Fellow of the British Academy (2008). RSS Guy Medals in Bronze (1998) and Silver (2012). John M Chambers Statistical Software Award, 2007
From playlist Short Talks
Selecting the BEST Regression Model (Part D)
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
R - Path Analysis, Estimation, Fit Indices Part 2
Lecturer: Dr. Erin M. Buchanan Spring 2021 https://www.patreon.com/statisticsofdoom This video covers the beginnings of path analysis, thinking about estimation, and a whole lot of fit indices. You will get to learn about how path compares to regression, as well as how mediation is teste
From playlist Structural Equation Modeling 2020
