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Solutions Manual to accompany Introduction to Linear Regression Analysis

 E-Book
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ISBN-13:
9781118640807
Einband:
E-Book
Seiten:
162
Autor:
Douglas C. Montgomery
eBook Typ:
PDF
eBook Format:
E-Book
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:

As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.
Preface xiii
1. Introduction 1

2. Simple Linear Regression 13

3. Multiple Linear Regression 67

4. Model Adequacy Checking 131

5. Transformations and Weighting to Correct Model Inadequacies 173

6. Diagnostics for Leverage and Influence 207

7. Polynomial Regression Models 221

8. Indicator Variables 265

9. Variable Selection and Model Building 291

10. Multicollinearity 325

11. Robust Regression 382

12. Introduction to Nonlinear Regression 414

13. Generalized Linear Models 443

14. Other Topics in the Use of Regression Analysis 488

15. Validation of Regression Models 529

Appendix A. Statistical Tables 549

Appendix B. Data Sets For Exercises 567

Appendix C. Supplemental Technical Material 582

References 621

Index 637
As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.

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