multiple linear regression is a regression method that models the relationship between a dependent variable Y, independent variables Xi, i = 1, ..., p, and a random term epsilon. The model can be written as
Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \cdots +\beta_p X_p + \varepsilon
where \beta_0 = 0 is the intercept ("constant" term), the \beta_i s are the respective parameters of independent variables, and p is the number of parameters to be estimated in the linear regression.