The First Edition of Modeling Regression: Methods, Theory, and Computation with SAS describes both the conventional and less common uses of almost all the regression types in the practical context of today's mathematical, economic and scientific research. This book is designed to introduce the reader to the richness and diversity of regression techniques and is particularly well suited for use in a second course in statistics at the undergraduate or first-year graduate level. This book is a robust resource that offers solid methodology for statistical practitioners and professionals in this field and it is also ideal for students of the applied mathematics or statistics, sciences, economics, and engineering who routinely use regression analysis for decision making and problem solving. Scientists and engineers will find the book to be an excellent choice for reference and self-study. This book blends both theory and application to equip the reader with an understanding of the principles necessary to apply regression model-building techniques in the SAS environment.