Ebook: Regression Analysis: Theory, Methods, and Applications

Any method of fitting equations to data may be called regression. Such equations are valuable for at least two purposes: making predictions and judging the strength of relationships. Because they provide a way of em­ pirically identifying how a variable is affected by other variables, regression methods have become essential in a wide range of fields, including the social sciences, engineering, medical research and business. Of the various methods of performing regression, least squares is the most widely used. In fact, linear least squares regression is by far the most widely used of any statistical technique. Although nonlinear least squares is covered in an appendix, this book is mainly about linear least squares applied to fit a single equation (as opposed to a system of equations). The writing of this book started in 1982. Since then, various drafts have been used at the University of Toronto for teaching a semester-long course to juniors, seniors and graduate students in a number of fields, including statistics, pharmacology, engineering, economics, forestry and the behav­ ioral sciences. Parts of the book have also been used in a quarter-long course given to Master's and Ph.D. students in public administration, urban plan­ ning and engineering at the University of Illinois at Chicago (UIC). This experience and the comments and criticisms from students helped forge the final version.

---

This book gives an up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis. It is ideally suited for those interested in the theory of regression analysis as well as to those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines showing the difficulties typically encountered in the practice of the craft of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject. "I found this to be the most complete and up-to-date regression text I have come across...this text has much to offer." Journal of the American Statistical Association "The material is presented in a lucid and easy-to-understand style...can be ranked as one of the best textbooks on regression in the market." Mathematical Reviews "...a successful mix of theory and practice...It will serve nicely to teach both the logic behind regression and the data-analytic use of regression." SIAM Review

---

This book gives an up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis. It is ideally suited for those interested in the theory of regression analysis as well as to those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines showing the difficulties typically encountered in the practice of the craft of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject. "I found this to be the most complete and up-to-date regression text I have come across...this text has much to offer." Journal of the American Statistical Association "The material is presented in a lucid and easy-to-understand style...can be ranked as one of the best textbooks on regression in the market." Mathematical Reviews "...a successful mix of theory and practice...It will serve nicely to teach both the logic behind regression and the data-analytic use of regression." SIAM Review
Content:
Front Matter....Pages i-xv
Introduction....Pages 1-27
Multiple Regression....Pages 28-59
Tests and Confidence Regions....Pages 60-82
Indicator Variables....Pages 83-99
The Normality Assumption....Pages 100-110
Unequal Variances....Pages 111-131
*Correlated Errors....Pages 132-153
Outliers and Influential Observations....Pages 154-179
Transformations....Pages 180-217
Multicollinearity....Pages 218-232
Variable Selection....Pages 233-252
*Biased Estimation....Pages 253-264
Back Matter....Pages 265-347

---

This book gives an up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis. It is ideally suited for those interested in the theory of regression analysis as well as to those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines showing the difficulties typically encountered in the practice of the craft of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject. "I found this to be the most complete and up-to-date regression text I have come across...this text has much to offer." Journal of the American Statistical Association "The material is presented in a lucid and easy-to-understand style...can be ranked as one of the best textbooks on regression in the market." Mathematical Reviews "...a successful mix of theory and practice...It will serve nicely to teach both the logic behind regression and the data-analytic use of regression." SIAM Review
Content:
Front Matter....Pages i-xv
Introduction....Pages 1-27
Multiple Regression....Pages 28-59
Tests and Confidence Regions....Pages 60-82
Indicator Variables....Pages 83-99
The Normality Assumption....Pages 100-110
Unequal Variances....Pages 111-131
*Correlated Errors....Pages 132-153
Outliers and Influential Observations....Pages 154-179
Transformations....Pages 180-217
Multicollinearity....Pages 218-232
Variable Selection....Pages 233-252
*Biased Estimation....Pages 253-264
Back Matter....Pages 265-347
....