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100   $a20160829d2001      uy             0
101 0 $aeng
200 10$aApplied multivariate data analysis$b[electronic resource] /$fBrian S. Everitt and Graham Dunn
205   $a2nd ed.
210   $aChichester $cWiley$d2001
215   $a1 online resource (x, 342 p.) $cill
300   $aFirst published by Arnold.
311   $a0-470-71117-5 
327   $a1. Multivariate Data and Multivariate Statistics -- 2. Exploring Multivariate Data Graphically -- 3. Principal Components Analysis -- 4. Correspondence Analysis -- 5. Multidimensional Scaling -- 6. Cluster Analysis -- 7. The Generalized Linear Model -- 8. Regression and the Analysis of Variance -- 9. Log?Linear and Logistic Models for Categorical Multivariate Data -- 10. Models for Multivariate Response Variables -- 11. Discrimination, Classification and Pattern Recognition -- 12. Exploratory Factor Analysis -- 13. Confirmatory Factor Analysis and Covariance Structure Models -- Appendix A: Software Packages -- Appendix B: Missing Values -- Appendix C: Answers to Selected Exercises -- References -- Index.
330   $aMultivariate analysis plays an important role in the understanding of complex data sets requiring simultaneous examination of all variables. Breaking through the apparent disorder of the information, it provides the means for both describing and exploring data, aiming to extract the underlying patterns and structure. This intermediate-level textbook introduces the reader to the variety of methods by which multivariate statistical analysis may be undertaken. Now in its 2nd edition, 'Applied Multivariate Data Analysis' has been fully expanded and updated, including major chapter revisions as well as new sections on neural networks and random effects models for longitudinal data. Maintaining the easy-going style of the first edition, the authors provide clear explanations of each technique, as well as supporting figures and examples, and minimal technical jargon. With extensive exercises following every chapter, 'Applied Multivariate Data Analysis' is a valuable resource for students on applied statistics courses and applied researchers in many disciplines.
606   $aMultivariate analysis
615  0$aMultivariate analysis.
676   $a519.535
700   $aEveritt$b Brian$056108
701   $aDunn$b G$g(Graham),$f1949-$06606
906   $aBOOK
912   $a9910830713503321
996   $aApplied multivariate data analysis$9694072
997   $aUNINA