After reading this chapter you will understand:
In this chapter we continue with our coverage of multiple linear regression analysis. The topics covered in this chapter are the problem of multicollinearity, model building techniques using stepwise regression analysis, and testing the assumptions of the models that were described in Chapter 3.
When discussing the suitability of a model, an important issue is the structure or interaction of the independent variables. The statistical term used for the problem that arises from the high correlations among the independent variables used in a multiple regression model is multicollinearity or, simply, collinearity. Tests for the presence of multicollinearity must be performed after the model's significance has been determined and all significant independent variables to be used in the final regression have been determined.
A good deal of intuition ...