ABSTRACT
This chapter discusses: the characteristic features of a multiple linear regression model; reasons why you would want to use this model; how you can estimate the mean of Y as well as an individual Y value in a sampled population subgroup with a specific combination of values for the explanatory variables; ideal inference conditions for multiple linear regression and potential difficulties when these conditions are not met; collinearity and why it can be a concern when interpreting results; why it is critical to get a valid estimate of the variability of Y given the X variables; and how to apply a multiple linear regression analysis using the REG procedure in SAS software.
