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1. Introduction to Generalized Linear Models.
1.1 Linear Models.
1.2 Nonlinear Models.
1.3 The Generalized Linear Model.
2. Linear Regression Models.
2.1 The Linear Regression Model and Its Application.
2.2 Multiple Regression Models.
2.3 Parameter Estimation Using Maximum Likelihood.
2.4 Model Adequacy Checking.
2.5 Using R to Perform Linear Regression Analysis.
2.6 Parameter Estimation by Weighted Least Squares.
2.7 Designs for Regression Models.
3. Nonlinear Regression Models.
Douglas C. Montgomery, PhD, is Regents' Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery has more than thirty years of academic and consulting experience and has devoted his research to engineering statistics, specifically the design and analysis of experiments. He has authored or coauthored numerous journal articles and twelve books, including Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Third Edition; Introduction to Linear Regression Analysis, Fourth Edition; and Introduction to Time Series Analysis and Forecasting, all published by Wiley.
G. Geoffrey Vining, PhD, is Professor in the Department of Statistics at Virginia Polytechnic Institute and State University. A Fellow of both the American Statistical Association and the American Society for Quality, Dr. Vining is also the coauthor of Introduction to Linear Regression Analysis, Fourth Edition (Wiley).
Timothy J. Robinson, PhD, is Associate Professor in the Department of Statistics at the University of Wyoming. He has written numerous journal articles in the areas of design of experiments, response surface methodology, and applications of categorical data analysis in engineering, medicine, and the environmental sciences.