Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Linear regression models the relationship between a dependent and independent variable (s). A linear regression essentially estimates a line of best fit among all variables in the model.

One of the simplest prediction methods is linear regression, in which we attempt to find a 'best line' through the data points.

Lesson 9 Simple Linear Regression The purpose of this tutorial is to continue our exploration of multivariate statistics by conducting a simple (one explanatory variable) linear regression analysis.

Although [Vitor Fróis] is explaining linear regression because it relates to machine learning, the post and, indeed, the topic have wide applications in many things that we do with electronics ...

Lesson 10 Multiple Linear Regression The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an ...

Statistical texts written by geographers invariably illustrate and calculate the prediction limits about an estimated regression line as pairs of parallel lines. Such limits should be hyperbolic when ...

The developments in linear regression methodology that have taken place during the 25-year history of Technometrics are summarized. Major topics covered are variable selection, biased estimation, ...