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Synopsis
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.
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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.
"About this title" may belong to another edition of this title.
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