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• Cover
• Applied Regression Modeling
• Copyright
• Dedication
• Preface
• Acknowledgments
• Introduction
• About the Companion Website
• Chapter 1: Foundations
• 1.1 Identifying and Summarizing Data
• 1.2 Population Distributions
• 1.3 Selecting Individuals at Random—Probability
• 1.4 Random Sampling
• 1.5 Interval Estimation
• 1.6 Hypothesis Testing
• 1.7 Random Errors and Prediction
• 1.8 Chapter Summary
• Chapter 2: Simple Linear Regression
• 2.1 Probability Model for and
• 2.2 Least Squares Criterion
• 2.3 Model Evaluation
• 2.4 Model Assumptions
• 2.5 Model Interpretation
• 2.6 Estimation and Prediction
• 2.7 Chapter Summary
• Chapter 3: Multiple Linear Regression
• 3.1 Probability Model for (X1, X2, …) and Y
• 3.2 Least Squares Criterion
• 3.3 Model Evaluation
• 3.4 Model Assumptions
• 3.5 Model Interpretation
• 3.6 Estimation and Prediction
• 3.7 Chapter Summary
• Chapter 4: Regression Model Building I
• 4.1 Transformations
• 4.2 Interactions
• 4.3 Qualitative Predictors
• 4.4 Chapter Summary
• Chapter 5: Regression Model Building II
• 5.1 Influential Points
• 5.2 Regression Pitfalls
• 5.3 Model Building Guidelines
• 5.4 Model Selection
• 5.5 Model Interpretation Using Graphics
• 5.6 Chapter Summary
• Bibliography
• Glossary
• Index
• End User License Agreement