Iain Pardoe - Applied Regression Modeling

1 Cover

2 Applied Regression Modeling Applied Regression Modeling Third Edition Iain Pardoe Thompson Rivers University The Pennsylvania State University

3 Copyright

4 Dedication

5 Preface

6 Acknowledgments

7 Introduction

8 About the Companion Website

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

17 End User License Agreement

1 Chapter 3Table 3.1 Shipping data with response variable weekly labor hours and four p...

2 Chapter 4Table 4.1 TV commercial data: spending in $m, millions of retained impress...Table 4.2 Car data with city miles per gallon, engine size in liters, for

3 Chapter 5Table 5.1 Car data with miles per gallon, size (l), of cylinders, pass...Table 5.2 Computer component data.Table 5.3 Simulated dataset containing missing values.Table 5.4 Some automated model selection results for the SIMULATEdata fileTable 5.5 Credit card data to illustrate model interpretation using predictor...

1 Chapter 1 Figure 1.1 Histogram for home prices example. Figure 1.2 Histogram for a simulated population of sale prices, together w... Figure 1.3 Standard normal density curve together with a shaded area of be... Figure 1.4 QQ‐plot for the home prices example. Figure 1.5 The central limit theorem in action. The upper density curve (a) ... Figure 1.6 Home prices example—density curve for the t‐distribution with d... Figure 1.7 Relationships between critical values, significance levels, test ... Figure 1.8 Relationships between critical values, significance levels, test ...

2 Chapter 2 Figure 2.1 (a)–(d) Different kinds of association between sale price and flo... Figure 2.2 Scatterplot showing the simple linear regression model for the ho... Figure 2.3 Linear equation for the simple linear regression model. Figure 2.4 Illustration of the least squares criterion for the simple linear... Figure 2.5 Simple linear regression model fitted to sample data for the home... Figure 2.6 How well does the model fit each dataset?Figure 2.7 Interpretation of the regression standard error for simple linear...Figure 2.8 Measures of variation used to derive the coefficient of determina...Figure 2.9 Examples of values for a variety of scatterplots.Figure 2.10 Examples of correlation values and corresponding values for a ...Figure 2.11 Simple linear regression model fitted to hypothetical population...Figure 2.12 Illustration of the sampling distribution of the slope for the s...Figure 2.13 Scatterplot illustrating random error probability distributions....Figure 2.14 Examples of residual plots for which the four simple linear regr...Figure 2.15 Examples of residual plots for which the four simple linear regr...Figure 2.16 Examples of histograms of residuals for which the normality regr...Figure 2.17 Examples of QQ‐plots of residuals for which the normality regres...Figure 2.18 Simple linear regression model for the home prices–floor size ex...Figure 2.19 Scatterplot illustrating confidence intervals for the mean, , a...Figure 2.20 Scatterplot of standing height (in cm) and upper arm length ...Figure 2.21 Residual plot for the body measurements example.Figure 2.22 Histogram and QQ‐plot of residuals for the body measurements exa...Figure 2.23 Scatterplot of versus for the body measurements example with...Figure 2.242.24 Examples of residual plots for Problem 14.Figure 2.252.25 Examples of QQ‐plots for Problem 14.

3 Chapter 3Figure 3.1 Multiple linear regression model with two predictors fitted to a ...Figure 3.2 Scatterplot matrix for the home prices example.Figure 3.3 Scatterplot of simulated data with low correlation between