Regression Analysis by Example (Wiley Series in Probability and Statistics)

Description

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 analysisA new chapter entitled Further Topics discusses advanced areas of regression analysis Reorganized, expanded, and upgraded exercises appear at the end of each chapterA fully integrated Web page provides data setsNumerous 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. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.Summary: Great examples!Rating: 5Its strength is in the examples. It is true that the book also employs formulas, but most of them are informative and fairly easy to follow if you have a moderate background in statistics. I would recommend this book for an intermediate course in econometrics, mainly because it offers a comprehensive view of the subject and ways to apply analysis tools. I give it five stars for the presence of applied data.Summary: Thorough, but difficult to follow.Rating: 3I used this book for an introductory/intermediate course in regression. Although the authors presented a lot of material and I did find it informative, I found myself having to refer to other texts for a better explanation of about half of the material presented. To me it read like an academic paper. It seemed that all the variables were explained only once in the text and used throughout the book without a central glossary or formula page. There also seemed to be a lot of subscripts and superscripts to the variables, as well as bouncing back and forth between data examples, which made following the concepts difficult. There was a lot of information packed in the book's pages, but it was real difficult reading and trying to comprehend past the second chapter.

Enjoy this great book! Brought to you by SMIRK




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