For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. The eighth edition of Multivariate Data Analysis provides an updated perspective on the analysis of all types of data as well as introducing some new perspectives and techniques that are foundational in today's world of analytics.Multivariate Data Analysis serves as the perfect companion for graduate and postgraduate students undertaking statistical analysis for business degrees, providing an application-oriented introduction to multivariate analysis for the…mehr
For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. The eighth edition of Multivariate Data Analysis provides an updated perspective on the analysis of all types of data as well as introducing some new perspectives and techniques that are foundational in today's world of analytics.Multivariate Data Analysis serves as the perfect companion for graduate and postgraduate students undertaking statistical analysis for business degrees, providing an application-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.
Joseph F. Hair, Jr. is Cleverdon Chair of Business at University of South Alabama, USA. He previously held the Copeland Endowed Chair of Entrepreneurship and was Director of the Entrepreneurship Institute at the E.J. Ourso College of Business, Louisiana State University. He was a United States Steel Foundation Fellow at the University of Florida, Gainesville, where he earned his Ph.D. in Marketing. He has authored over 40 books and has published numerous articles in professional journals. He is a Distinguished Fellow of the Academy of Marketing Sciences, the Society for Marketing Advances, and the Southwestern Marketing Association.Barry J. Babin has authored more than 100 research publications in some of today's most prestigious peer-reviewed research periodicals, such as the Journal of Marketing, Journal of Consumer Research, Journal of Business Research, Journal of Retailing, Psychology and Marketing, Journal of the Academy of Marketing Science and the International Journal of Wine Business Research. Dr. Babin is currently Morris Lewis Professor of Marketing and chair of marketing in the Ole Miss Business School. He has won numerous honors for his research, including the Louis K. Brandt Faculty Research Award from the University of Southern Mississippi, Outstanding Researcher in the COB at Louisiana Tech University, the 1996 Society for Marketing Advances (SMA) Steven J. Shaw Award, the 1997 Omerre Deserres Award for Outstanding Contributions to Retail and Service Environment Research and the Academy of Marketing Science's prestigious Harold W. Berkman Distinguished Service Award. Dr. Babin is a past pre
sident of the Academy of Marketing Science and the Society for Marketing Advances and has been recognized as a distinguished fellow of both organizations. His research focuses on the effect of the service environment in creating value for employees and customers and on the impact of big data on consumer liberty. He offers expertise in building and understanding value that leads to long-lasting, mutually beneficial relationships with employees and customers. His teaching specialties involve advanced methods of marketing and consumer research and creative problem solving. A frequent international lecturer, he has presented in Australia, South Korea, France, Germany, Mexico, New Zealand, South Africa, Canada, Sweden, Norway, Peru, Israel and the United Kingdom.
Inhaltsangabe
Chapter 1 Overview of Multivariate MethodsSection 1: Preparing for Multivariate AnalysisChapter 2: Examining Your DataSection 2: Interdependence TechniquesChapter 3: Exploratory Factor AnalysisChapter 4: Cluster AnalysisSection 3: Dependence TechniquesChapter 5: Multiple RegressionChapter 6: MANOVA: Extending ANOVAChapter 7: Discriminant AnalysisChapter 8: Logistic Regression: Regression with a Binary Dependent VariableSection 4: Moving Beyond the Basic TechniquesChapter 9: Structural Equation Modeling: An IntroductionChapter 10: Confirmatory Factor AnalysisChapter 11: Testing Structural Equation ModelsChapter 12: Advanced Topics in SEMChapter 13: Partial Least Squares Modeling (PLS-SEM)In addition to the chapters in the print book, e-copies of all other chapters in the previous editions are available to download on the companion website, including canonical correlation, conjoint analysis, multidimensional scaling, and correspondence analysis.
Chapter 1 Overview of Multivariate MethodsSection 1: Preparing for Multivariate AnalysisChapter 2: Examining Your DataSection 2: Interdependence TechniquesChapter 3: Exploratory Factor AnalysisChapter 4: Cluster AnalysisSection 3: Dependence TechniquesChapter 5: Multiple RegressionChapter 6: MANOVA: Extending ANOVAChapter 7: Discriminant AnalysisChapter 8: Logistic Regression: Regression with a Binary Dependent VariableSection 4: Moving Beyond the Basic TechniquesChapter 9: Structural Equation Modeling: An IntroductionChapter 10: Confirmatory Factor AnalysisChapter 11: Testing Structural Equation ModelsChapter 12: Advanced Topics in SEMChapter 13: Partial Least Squares Modeling (PLS-SEM)In addition to the chapters in the print book, e-copies of all other chapters in the previous editions are available to download on the companion website, including canonical correlation, conjoint analysis, multidimensional scaling, and correspondence analysis.
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