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Practical Multivariate Analysis, Fifth Edition

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""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 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

Author(s): Afifi, Abdelmonem; Clark, Virginia A.; May, Susanne
Series: Chapman & Hall/CRC Texts in Statistical Science
Edition: 5th ed
Publisher: CRC Press
Year: 2011

Language: English
Pages: 530
City: Hoboken
Tags: Математика;Теория вероятностей и математическая статистика;Математическая статистика;Прикладная математическая статистика;

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