Multivariate Data Analysis: Pearson New International Edition
7th Edition
Published on 17. July 2013
Book
Paperback/Softback
740 pages
978-1-292-02190-4 (ISBN)
Description
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.
More details
Edition
7th edition
Language
English
Place of publication
Harlow
United Kingdom
Target group
College/higher education
Dimensions
Height: 275 mm
Width: 215 mm
Thickness: 40 mm
Weight
1781 gr
ISBN-13
978-1-292-02190-4 (9781292021904)
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Schweitzer Classification
Other editions
Previous edition
Book
03/2009
7th Edition
Pearson Education (US)
€181.97
Article exhausted; check for reprint
Content
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
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