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
An Introduction to Linear Regression Analysis
Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Lon
From playlist Linear Regression.
Simple Linear Regression Formula, Visualized | Ch.1
In this video, I will guide you through a really beautiful way to visualize the formula for the slope, beta, in simple linear regression. In the next few chapters, I will explain the regression problem in the context of linear algebra, and visualize linear algebra concepts like least squa
From playlist From Linear Regression to Linear Algebra
(ML 9.2) Linear regression - Definition & Motivation
Linear regression arises naturally from a sequence of simple choices: discriminative model, Gaussian distributions, and linear functions. A playlist of these Machine Learning videos is available here: http://www.youtube.com/view_play_list?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
Intro to Linear Systems: 2 Equations, 2 Unknowns - Dr Chris Tisdell Live Stream
Free ebook http://tinyurl.com/EngMathYT Basic introduction to linear systems. We discuss the case with 2 equations and 2 unknowns. A linear system is a mathematical model of a system based on the use of a linear operator. Linear systems typically exhibit features and properties that ar
From playlist Intro to Linear Systems
“Choice Modeling and Assortment Optimization” - Session II - Prof. Huseyin Topaloglu
This module overviews static and dynamic assortment optimization problems. We will start with an introduction to discrete choice modeling and discuss estimation issues when fitting a choice model to observed sales histories. Following this introduction, we will discuss static and dynamic a
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
Statistical Rethinking - Lecture 13
Lecture 13 - Generalized Linear Models (intro) - Statistical Rethinking: A Bayesian Course with R Examples
From playlist Statistical Rethinking Winter 2015
Truths Behind the Titanic : Regressions
Logistic, Adapted Linear, Lasso Regression Models
From playlist Truths Behind the Titanic
Statistical Rethinking 2022 Lecture 03 - Geocentric Models
Linear regression from a Bayesian perspective Slides and course materials: https://github.com/rmcelreath/stat_rethinking_2022 Music Intro: https://www.youtube.com/watch?v=4y33h81phKU Flow: https://www.youtube.com/watch?v=ip4n8zaTg1w Pause: https://www.youtube.com/watch?v=1f-NQAgm-YM Cha
From playlist Statistical Rethinking 2022
Statistical Rethinking Fall 2017 - week07 lecture12
Week 07, lecture 12 for Statistical Rethinking: A Bayesian Course with Examples in R and Stan, taught at MPI-EVA in Fall 2017. This lecture covers Chapter 10. Slides are available here: https://speakerdeck.com/rmcelreath Additional information on textbook and R package here: http://xce
From playlist Statistical Rethinking Fall 2017
Why The Best Data Scientists have Mastered Algebra, Calculus and Probability
All the outstanding data scientist and ML engineers have one thing in common: They have a strong, working understanding of how ML's high-level software libraries work. Being able to look under the hood, and understand what's going in libraries such as scikit-learn, TensorFlow, and Keras,
From playlist Talks and Tutorials
03 02 Part 1 of 3 Logistic regression
From playlist Coursera Regression V2
11d Machine Learning: Bayesian Linear Regression
Lecture on Bayesian linear regression. By adopting the Bayesian approach (instead of the frequentist approach of ordinary least squares linear regression) we can account for prior information and directly model the distributions of the model parameters by updating with training data. Foll
From playlist Machine Learning
Statistical Rethinking Winter 2019 Lecture 11
Lecture 11 of the Dec 2018 through March 2019 edition of Statistical Rethinking: A Bayesian Course with R and Stan. Covers Chapters 10 and 11: maximum entropy, generalized linear models.
From playlist Statistical Rethinking Winter 2019
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