Linear regression algorithms fit a straight line, or another function that is linear in its parameters such as a polynomial, to numeric data, typically by performing matrix inversions to minimize ...

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 extension of Lesson 9.

Linda M. Haines, The Application of the Annealing Algorithm to the Construction of Exact Optimal Designs for Linear-Regression Models, Technometrics, Vol. 29, No. 4 (Nov., 1987), pp. 439-447 ...

Linear regression draws corresponding trend lines, such as disease outbreaks, bitcoin prices, demand for software experts, etc.