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Full Description
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.
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
