Table of Contents
1 Cover
5 Preface
9 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
10 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
11 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
12 Chapter 4: Regression Model Building I 4.1 Transformations 4.2 Interactions 4.3 Qualitative Predictors 4.4 Chapter Summary
13 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
14 Bibliography
15 Glossary
16 Index
List of Tables
1 Chapter 3Table 3.1 Shipping data with response variable
2 Chapter 4Table 4.1 TV commercial data:
3 Chapter 5Table 5.1 Car data with
List of Illustrations
