The concepts behind linear regression, fitting a line to data with least squares and R-squared, are pretty darn simple, so let's get down to it! NOTE: This StatQuest comes with a companion video for how to do linear regression in R: https://www.youtube.com/watch?v=u1cc1r_Y7M0 You can also find example code at the StatQuest github: https://github.com/StatQuest/linear_regression_demo If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: null ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:37 The Main Ideas!!! 1:12 Review of fitting a line to data 4:00 Review of R-squared 12:13 R-squared for a multivariable model 14:16 Why adding variables will never reduce R-squared 16:08 Calculating a p-value for R-squared 25:26 The F-distribution Correction: 25:39 I should have (Pfit - Pmean) instead of the other way around. #statquest #regression