Practical Multivariate Analysis, Fifth Edition

""First of all, it is very easy to read. ... The authors manage to introduce and (at least partially) explain even quite complex concepts, e.g. eigenvalues, in an easy and pedagogical way that I suppose is attractive to readers without deeper statistical knowledge. The text is also sprinkled with references for those who want to probe deeper into a certain topic. Secondly, I personally find the book's emphasis on practical data handling very appealing. ... Thirdly, the book gives very nice coverage of regression analysis. ... this is a nicely written book that gives a good overview of a large number. Read more... Abstract: ""First of all, it is very easy to read. ... The authors manage to introduce and (at least partially) explain even quite complex concepts, e.g. eigenvalues, in an easy and pedagogical way that I suppose is attractive to readers without deeper statistical knowledge. The text is also sprinkled with references for those who want to probe deeper into a certain topic. Secondly, I personally find the book's emphasis on practical data handling very appealing. ... Thirdly, the book gives very nice coverage of regression analysis. ... this is a nicely written book that gives a good overview of a large number Front Cover 1 Contents 8 Preface 16 Authors' Biographies 20 I. Preparation for Analysis 22 1. What is multivariate analysis? 24 2. Characterizing data for analysis 36 3. Preparing for data analysis 44 4. Data screening and transformations 68 5. Selecting appropriate analyses 88 II. Applied Regression Analysis 100 6. Simple regression and correlation 102 7. Multiple regression and correlation 140 8. Variable selection in regression 180 9. Special regression topics 210 III. Multivariate Analysis 242 10. Canonical correlation analysis 244 11. Discriminant analysis 260 12. Logistic regression 290 13. Regression analysis with survival data 344 14. Principal components analysis 378 15. Factor analysis 400 16. Cluster analysis 426 17. Log-linear analysis 452 18. Correlated outcomes regression 484 Appendix A 512 References 516 Content: Front Cover Contents Preface Authors' Biographies I. Preparation for Analysis 1. What is multivariate analysis? 2. Characterizing data for analysis 3. Preparing for data analysis 4. Data screening and transformations 5. Selecting appropriate analyses II. Applied Regression Analysis 6. Simple regression and correlation 7. Multiple regression and correlation 8. Variable selection in regression 9. Special regression topics III. Multivariate Analysis 10. Canonical correlation analysis 11. Discriminant analysis 12. Logistic regression 13. Regression analysis with survival data 14. Principal components analysis15. Factor analysis 16. Cluster analysis 17. Log-linear analysis 18. Correlated outcomes regression Appendix A References This new version of the bestselling Computer-Aided Multivariate Analysis has been appropriately renamed to better characterize the nature of the book. Taking into account novel multivariate analyses as well as new options for many standard methods, Practical Multivariate Analysis, Fifth Edition shows readers how to perform multivariate statistical