An Interpretation of the Least Squares Regression Surface

A pedagogically useful interpretation of the least squares regression surface is offered.In particular, it is shown that the least squares hyperplane can be viewed as the weighted average of all of the possible hyperplanes that can be formed by observational set combinations.The appropriate weighting scheme is developed, and two examples are presented.Furthermore, the notions of robustness and influential observations are simply explained.