Multivariate data analysis / Joseph F. Hair, Jr. ... [et al.]

Includes bibliographical references and index.

I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance IV Interdependence Techniques 7 Cluster Analysis 8 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 9 Structural Equation Modeling: Overview 10 Appendix - SEM 10a CFA: Confirmatory Factor Analysis 11 Appendix - CFA 11a SEM: Testing A Structural Model 12 Appendix - SEM 12a Conjoint Analysis APPENDIX A Basic Stats. :Pearson New International Edition.

For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. This text provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques. In this revision, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques. :Pearson New International Edition.