Regression Analysis by Example, Second Edition

A variety of ideas and methods of regression analysis are explored with the aid of realistic examples that highlight the analysis of data and include irregularities similar to those encountered in practice. Recent advances in regression diagnostics are covered with emphasis on plots such as component plus residual, added variable, sequence, along with index plots for leverage and function. The authors utilize standard and some not so standard summary statistics on the basis of their intuitive appeal to demonstrate concepts. The majority of analyses described are available in software packages on the market today.

The essentials of regression analysis through practical applications

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgement. Regression Analysis by Example, Fourth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression.

This new edition features the following enhancements:

• Chapter 12, Logistic Regression, is expanded to reflect the increased use of the logit models in statistical analysis
• A new chapter entitled Further Topics discusses advanced areas of regression analysis
• Reorganized, expanded, and upgraded exercises appear at the end of each chapter
• A fully integrated Web page provides data sets
• Numerous graphical displays highlight the significance of visual appeal

Regression Analysis by Example, Fourth Edition is suitable for anyone with an understanding of elementary statistics. Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. Each example isolates one or two techniques and features detailed discussions of the techniques themselves, the required assumptions, and the evaluated success of each technique. The methods described throughout the book can be carried out with most of the currently available statistical software packages, such as the software package R.