Using an accessible, nontechnical approach, the third edition of Regression Basics introduces readers to the fundamentals of statistical regression. Accessible to anyone with an introductory statistics background, the book draws on engaging examples using real-world data and software programs SPSS®, Stata®, and R to illustrate the key concepts of the least squares regression methodology.
The book emphasizes the intuition of regression methodology and provides a hands-on approach, as well as helpful end-of-chapter summaries and questions to consolidate learning. This new edition has been substantially revised and enhanced, with features including the following:
- Fully updated to show procedures in R, SPSS®, and Stata®
- Color images and substantially revised visual presentation
- A suite of online resources including data sets, software instructions, and PowerPoint slides for instructors
- New and updated examples throughout
- Expanded material to help students overcome "math anxiety"
- Expanded material on multicollinearity, heteroskedasticity, and robust standard errors
This well-paced book is ideal for advanced undergraduate and graduate students focusing on quantitative methods, research design, and statistical regression in the social and behavioral sciences, political science, and economics.
Table of Contents:
1. Introduction 2. An Introduction to the Linear Regression Model 3. The Least Squares Estimation Method 4. Model Performance and Evaluation 5. The Multiple Regression Model 6. Nonlinear and Logarithmic Models and Dummy and Interaction Variables 7.Time Series and Panel Data: An Introduction 8. Some Common Problems in Regression Analysis 9. Where to Go from Here Appendix A: t Table
About the Author :
Leo H. Kahane is the Michael A. Ruane Distinguished Chair in Economics at Providence College in Rhode Island, USA. He earned his BA degree in economics at the University of California, Berkeley, and his PhD degree in economics at Columbia University. He is the author/editor of multiple books, various book chapters, and dozens of peer-reviewed journal articles. He is also the founding editor of the Journal of Sports Economics.
Review :
“Regression Basics by Leo Kahane does a very strong job in alternating between theory and practice. For example, linear regression modeling is taught from a practical and also from an algorithmic perspective. The book has a nice gradual format, building from simple linear regression theory and practice, to multiple linear regression theory and practice, to nonlinear, panel, and time series theory and practice. The examples are appropriate and engaging, and Kahane’s writing is expert in keeping the reader engaged toward a comprehensive understanding of regression basics.
I also like that the book mixes examples from different industries, including professional sport, politics, real estate, and beyond.
In the closing chapter, Dr. Kahane does well in helping the reader understand how to build upon the foundation that the book provides.” -- Shane Sanders, Ph.D. Professor, Sports Economics & Analytics, Falk College, Syracuse University, USA
“Regression Basics by Leo Kahane is highly readable without sacrificing rigor or breadth. It covers all the main regression models for an undergraduate or early graduate course while maintaining a readable voice. Even the statistical syntax/exposition is laid out comprehensively but in a fashion that will not dissuade the reader from deeper study of regression modelling. I would recommend this book to professors of undergraduate econometrics, as well as MBA or Masters of economics courses. The supplementary materials allow for straightforward lab sessions with the students. I highly recommend this book.” -- Bhavneet Walia, Ph.D., , Falk College, Department of Public Health, Syracuse University, USA
