Multiple linear regression is a technique used to train a linear model, that assumes that there are linear relationships between multiple predictor variables (
) and a continuous target variable (
). The general equation for a multiple linear regression with m predictor variables is as follows:
Training a linear regression model involves estimating the values of the coefficients for each of the predictor variables denoted by the letter 
. In the preceding equation, 
denotes an error term, which is normally distributed, and has zero mean and constant variance. This is represented as follows:
Various techniques can be used to build a linear regression model. The most frequently used is the ordinary least square (OLS) estimate. The OLS method is used to produce a linear regression line...
