Multivariate Data Analysis
International Edition
5th Edition
Published on 7. April 1998
Book
Paperback/Softback
768 pages
978-0-13-930587-0 (ISBN)
Description
For graduate-level courses in Marketing Research, Research Design and Data Analysis . Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis greatly reduces the amount of statistical notation and terminology used while focusing instead on the fundamental concepts that affect the use of specific techniques.
More details
Edition
5th edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 253 mm
Width: 204 mm
Thickness: 34 mm
Weight
1388 gr
ISBN-13
978-0-13-930587-0 (9780139305870)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Book
11/2005
6th Edition
Pearson
€173.31
Article exhausted; check for reprint
Previous edition
Book
11/1994
4th Edition
Prentice-Hall
€32.13
Article exhausted; check for reprint
Content
1. Introduction.
I. PREPARING FOR A MULTIVARIATE ANALYSIS.
2. Examining Your Data.
3. Factor Analysis.
II. DEPENDENCE TECHNIQUES.
4. Multiple Regression.
5. Multiple Discriminant Analysis and Logistic Regression.
6. Multivariate Analysis of Variance.
7. Conjoint Analysis.
8. Canonical Correlation Analysis.
III. INTERDEPENDENCE TECHNIQUES.
9. Cluster Analysis.
10. Multidimensional Scaling.
IV. ADVANCED AND EMERGING TECHNIQUES.
11. Structural Equation Modeling.
12. Emerging Techniques in Multivariate Analysis.
Appendix A: Applications of Multivariate Data Analysis.
Index.
I. PREPARING FOR A MULTIVARIATE ANALYSIS.
2. Examining Your Data.
3. Factor Analysis.
II. DEPENDENCE TECHNIQUES.
4. Multiple Regression.
5. Multiple Discriminant Analysis and Logistic Regression.
6. Multivariate Analysis of Variance.
7. Conjoint Analysis.
8. Canonical Correlation Analysis.
III. INTERDEPENDENCE TECHNIQUES.
9. Cluster Analysis.
10. Multidimensional Scaling.
IV. ADVANCED AND EMERGING TECHNIQUES.
11. Structural Equation Modeling.
12. Emerging Techniques in Multivariate Analysis.
Appendix A: Applications of Multivariate Data Analysis.
Index.