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Regression Basics

Regression Basics

Second Edition

November 2007 | 240 pages | SAGE Publications, Inc

Using a friendly, nontechnical approach, the Second Edition of Regression Basics introduces readers to the fundamentals of regression. Accessible to anyone with an introductory statistics background, this book builds from a simple two-variable model to a model of greater complexity. Author Leo H. Kahane weaves four engaging examples throughout the text to illustrate not only the techniques of regression but also how this empirical tool can be applied in creative ways to consider a broad array of topics.

New to the Second Edition

Offers greater coverage of simple panel-data estimation: Because the availability of panel data has increased over the past decade, this new edition includes coverage of estimation with multiple cross-sections of data across time.

Provides an introductory discussion of omitted variables bias: As a problem that frequently arises, this issue is important for those new to regression analysis to understand.

Includes up-to-date advances: Chapter 7 is expanded to include recent developments in regression.

Uses a diverse selection of examples: Engaging examples illustrate the wide application of regression analysis from baseball salaries to presidential voting to British crime rates to U.S. abortion rates and more.

Includes more end-of-chapter problems: This edition offers new questions at the end of chapters that are based on the new examples woven through the book.

Illustrates examples using software programs: Appendix B now includes screenshots to further aid readers working with Microsoft Excel® and SPSS.

Intended Audience

This is an ideal core or supplemental text for advanced undergraduate and graduate courses such as Regression and Correlation, Sociological Research Methods, Quantitative Research Methods, and Statistical Methods in the fields of economics, public policy, political science, sociology, public affairs, urban planning, education, and geography.

1. An Introduction to the Linear Regression Model
2. The Least-Squares Estimation Method: Fitting Lines to Data
3. Model Performance And Evaluation
4. Multiple Regression Analysis
5. Non-Linear and Logarithmic Models, Dummy and Interaction
6. Time Variables and Panel Data: A Simple Introduction
7. Some Common Problems In Regression Analysis
8. Where To Go From Here
Appendix A: Data Sets Used In Examples
Appendix B: Instructions for Using Excel and SPSS
Appendix C: t Table
Appendix D: Answers To Problems

A really clear introduction to regression, well-pitched for graduate students. The introductory chapters provide an excellent background to the more advanced topics, e.g. on interactions. It's also slim and light enough to carry around and dip in and out of.

Dr Sunjeev Kamboj
Research Department of Clinical, Eductional and Health Psychology, University College London
August 22, 2014

A short volume but provides all the basics. Clearly presented. An excellent introduction.

Dr Sunjeev Kamboj
Research Department of Clinical, Eductional and Health Psychology, University College London
December 21, 2013

Excellent book. easy to read and very useful examples

Dr William McCluskey
Dept of the Built Environment, Ulster University
April 25, 2012

Although the book has at times a few informative graphical representations, I feel it might not be concrete enough for my students.

Dr Johan Braeken
Departement of Methodology & Statistics, Tilburg University
March 22, 2012

Suitable to use and purpose

Dr Paschal Anosike
Human Resources Management, Wolverhampton University
October 11, 2010

This book was easy to understand for undergraduate students and served as a good introduction to basic regression analysis used in Econometrics. A few simple data sets provided by the text provided continuity between the chapters, but additional data sets are needed to provide students with more practical experience. It is helpful to have a more extensive econometrics text on reserve for students as a reference. Instructors are will likely want to supplement the book with supplementary materials in order to cover some topics more extensively like Time Series and Logistic Regressions.

Professor Paul Bartlett
Economics Finance Dept, St Peters College
April 12, 2010
Key features
  • This new edition includes coverage of estimation with multiple cross-sections of data across time (panel data).
  • Chapter 7 has been expanded to include recent developments in regression.
  • This edition includes more end-of-chapter problems based on the examples that are woven through the book.
  • Appendix B now includes screen shots to further aid readers with working with Microsoft® Excel® and SPSS.



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