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This book is intended as a text for a basic course in linear regression analysis. It contains the standard topics as well as some of the newer and more unconventional ones and blends both theory and application so that the reader will obtain and understanding of the basic principles necessary to apply regression methods in a variety of practical settings. Foreword Preface Acknowledgments Part I Problems On Words ? Data Structures and Algorithms on Words ? Probabilistic and Analytical Models Part II Probabilistic And Combinatorial Techniques ? Inclusion-Exclusion Principle ? The First and Second Moment Methods ? Sub additive Ergodic Theorem and Large Deviations ? Elements of Information Theory Part III Analytic Techniques ? Generating Functions ? Complex Asymptotic Methods ? Mellin Transform and Its Applications ? Analytic Poissonization and Depoissonization Bibliography Index Douglas C. Montgomery is Professor in the Department of Industrial Engineering, Arizona State University. Elizabeth A. Peck is Logistics Modeling Specialist at the Coca-Cola Company in Atlanta, Georgia. G. Geoffrey Vining is Professor and Head of the Department of Statistics, Virginia Tech. ? Practitioners in diverse fields, including engineers, who use regression analysis techniques
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