Multiple Regression (MR) evaluates the relationship between a continuous response variable (Y) and two or more independent explanatory variables (Xs) by determining an equation to estimate the outcome of interest from knowledge of the multiple input variables.
MR results in an equation (called the regression equation or model) of the form:
Y = b0+ b1X1 + b2X2 + .... + ε
Y = the response (output) variable of interest
And the bi’s are the regression coefficients:
b0 = the mean of Y when all the Xs are set to zero
b1 = the change in the mean of Y for a one unit increase in the value of X1 (holding all other Xs constant)
b2 = the change in the mean of Y for a one unit increase in the value of X2 (holding all other Xs constant)
…. and so on …..
ε = the random error term