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Understanding Regression Analysis
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Understanding Regression Analysis
An Introductory Guide

Second Edition


January 2017 | 120 pages | SAGE Publications, Inc
Understanding Regression Analysis: An Introductory Guide presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style. It illustrates how regression coefficients are estimated, interpreted, and used in a variety of settings within the social sciences, business, law, and public policy. Packed with applied examples and using few equations, the book walks readers through elementary material using a verbal, intuitive interpretation of regression coefficients, associated statistics, and hypothesis tests. The Second Edition features updated examples and new references to modern software output.
 
Series Editor’s Introduction
 
Preface
 
Acknowledgments
 
About the Authors
 
1. Linear Regression
Introduction

 
Hypothesized Relationships

 
A Numerical Example

 
Estimating a Linear Relationship

 
Least Squares Regression

 
Examples

 
The Linear Correlation Coefficient

 
The Coefficient of Determination

 
Regression and Correlation

 
Summary

 
 
2. Multiple Linear Regression
Introduction

 
Estimating Regression Coefficients

 
Standardized Coefficients

 
Associated Statistics

 
Examples

 
Summary

 
 
3. Hypothesis Testing
Introduction

 
Concepts Underlying Hypothesis Testing

 
The Standard Error of the Regression Coefficient

 
The Student’s t Distribution

 
Left-Tail Tests

 
Two-Tail Tests

 
Confidence Intervals

 
F Statistic

 
What Tests of Significance Can and Cannot Do

 
Summary

 
 
4. Extensions to the Multiple Regression Model
Introduction

 
Types of Data

 
Dummy Variables

 
Interaction Variables

 
Transformations

 
Prediction

 
Examples

 
Summary

 
 
5. Problems and Issues Associated With Regression
Introduction

 
Specification of the Model

 
Variables Used in Regression Equations and Measurement of Variables

 
Violations of Assumptions Regarding Residual Errors

 
Additional Topics

 
Conclusions

 
 
Appendix A: Derivation of a and b
 
Appendix B: Critical Values for Student’s t Distribution
 
Appendix C: Regression Output From SAS, Stata, SPSS, R, and EXCEL
 
Appendix D: Suggested Textbooks
 
References
 
Index

“This is an excellent update; a clear and accessible introduction to a complex, yet very important, statistical method: regression analysis. The book can serve as a perfect supplement or stand-alone book in introductory social statistics courses.”

Grigoris Argeros
Eastern Michigan University

Understanding Regression Analysis provides students at all levels a foundational understanding of multiple linear regression analysis through intuitive explanations and interdisciplinary examples aimed at elucidating concepts, approaches, and interpretations.”

Andrea Hetling
Rutgers University – New Brunswick

“This monograph provides a clear and concise introduction to regression analysis concepts and procedures, with a problem-solving approach toward addressing common maladies of regression modeling.”

Ross E. Burkhart
Boise State University

“The authors do a top-notch job of competently presenting a plethora of topics regarding regression analysis.”

Wyatt Brown
University of South Florida

Sample Materials & Chapters

Chapter 1


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