Multivariate Data Analysis
Autor Joseph Hair, Rolph Anderson, Barry Babinen Limba Engleză Paperback – 31 ian 2009
For over 30 years, "Multivariate Data Analysis" has provided readers with the information they need to understand and apply multivariate data analysis.
Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques.
In this Seventh Edition, 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."
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Specificații
ISBN-13: 9780138132637
ISBN-10: 0138132631
Pagini: 785
Dimensiuni: 211 x 251 x 36 mm
Greutate: 1.57 kg
Ediția:7Nouă
Editura: Prentice Hall
Locul publicării:Upper Saddle River, United States
ISBN-10: 0138132631
Pagini: 785
Dimensiuni: 211 x 251 x 36 mm
Greutate: 1.57 kg
Ediția:7Nouă
Editura: Prentice Hall
Locul publicării:Upper Saddle River, United States
Cuprins
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
7 Conjoint Analysis
IV Interdependence Techniques
8 Cluster Analysis
9 Multidimensional Scaling and Correspondence Analysis
V Moving Beyond the Basic Techniques
10 Structural Equation Modeling: Overview
10a Appendix – SEM
11 CFA: Confirmatory Factor Analysis
11a Appendix – CFA
12 SEM: Testing A Structural Model
12a Appendix – SEM
APPENDIX
A Basic Stats
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
7 Conjoint Analysis
IV Interdependence Techniques
8 Cluster Analysis
9 Multidimensional Scaling and Correspondence Analysis
V Moving Beyond the Basic Techniques
10 Structural Equation Modeling: Overview
10a Appendix – SEM
11 CFA: Confirmatory Factor Analysis
11a Appendix – CFA
12 SEM: Testing A Structural Model
12a Appendix – SEM
APPENDIX
A Basic Stats
Caracteristici
For graduate and upper-level undergraduate marketing research courses.
For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.
Hair et. al 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 seventh 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.
NEW! Chapter Reorganization: Chapters now focus on a single topic and begin with providing basic information and application techniques. This is followed by more in-depth discussions later in the chapter.
NEW! “Rule of Thumb” Feature Expanded: This feature has been improved so students learn how to best use different techniques.
Use of Technical Terms and Statistical Notation Minimized: In order to make the text more accessible to management and non-mathematically focused students, the authors explain complex techniques in everyday language.
NEW! Additional Chapters: Structural Equations Modeling has been expanded and reorganized, now covering 4 chapters.
Other topics of distinction
NEW! Expansion of Website: “Great Ideas in Teaching Multivariate” Statistics has been updated to provide even more links for students and resources for instructors. There are a number of teaching materials available, including exercises, datasheets, and project ideas. The website can be found at www.mvstats.com
For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis.
Hair et. al 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 seventh 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.
NEW! Chapter Reorganization: Chapters now focus on a single topic and begin with providing basic information and application techniques. This is followed by more in-depth discussions later in the chapter.
NEW! “Rule of Thumb” Feature Expanded: This feature has been improved so students learn how to best use different techniques.
Use of Technical Terms and Statistical Notation Minimized: In order to make the text more accessible to management and non-mathematically focused students, the authors explain complex techniques in everyday language.
NEW! Additional Chapters: Structural Equations Modeling has been expanded and reorganized, now covering 4 chapters.
Other topics of distinction
NEW! Expansion of Website: “Great Ideas in Teaching Multivariate” Statistics has been updated to provide even more links for students and resources for instructors. There are a number of teaching materials available, including exercises, datasheets, and project ideas. The website can be found at www.mvstats.com