En savoir plus
Informationen zum Autor DOUGLAS C. MONTGOMERY, PHD, is Regents Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery is the co-author of several Wiley books including Introduction to Linear Regression Analysis, 5th Edition. ELIZABETH A. PECK, PHD, is Logistics Modeling Specialist at the Coca-Cola Company in Atlanta, Georgia. G. GEOFFREY VINING, PHD, is Professor in the Department of Statistics at Virginia Polytechnic and State University. Dr. Peck is co-author of Introduction to Linear Regression Analysis, 5th Edition. Klappentext INTRODUCTION TO LINEAR REGRESSION ANALYSISA comprehensive and current introduction to the fundamentals of regression analysisIntroduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book.The new edition focuses on four key areas of improvement over the fifth edition:* New exercises and data sets* New material on generalized regression techniques* The inclusion of JMP software in key areas* Carefully condensing the text where possibleIntroduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today's cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Zusammenfassung INTRODUCTION TO LINEAR REGRESSION ANALYSISA comprehensive and current introduction to the fundamentals of regression analysisIntroduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book.The new edition focuses on four key areas of improvement over the fifth edition:* New exercises and data sets* New material on generalized regression techniques* The inclusion of JMP software in key areas* Carefully condensing the text where possibleIntroduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today's cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Inhaltsverzeichnis Preface xiii About the Companion Website xvi 1. Introduction 1 1.1 Regression and Model Building 1 1.2 Data Collection 5 1.3 Uses of Regression 9 1.4 Role of the Computer 10 2. Simple Linear Regression 12 2.1 Simple Linear Regression Model 12 2.2 Least-Squares Estimation of the Parameters 13 2.2.1 Estimation of ß0 and ß1 13 2.2.2 Properties of the Least-Squares Estimators and the Fitted Regression Model 18 2.2.3 Estimation of ¿2 20 2.2.4 Alternate Form of the Model 22 2.3 Hypothesis Testing on the Slope and Intercept 22 2.3.1 Use of t Tests 22 2.3.2 Testing Significance of Regression 24 2.3.3 Analysis of Variance 25 2.4 Interval Estimation in Simple Linear Regression 29 2.4.1 Confidence Intervals on ß0, ß1, and ¿2 29 2.4.2 Interval Estimation of the Mean Response 30 2.5 Prediction of New Observations 3...
