Analyzing multivariate data (CD)

Table of Contents:


1. Introduction;

2. Vectors and matrices;

3. Regression analysis

Part II. Analysis of Interpendence:

4. Principal components analysis;

5. Exploratory factor analysis;

6. Confirmatory factor analysis;

7. Multidimensional scaling;

8. Cluster analysis

Part III. Analysis of Dependence:

9. Canonical correlation;

10. Structural equation models with latent variables;

11. Analysis of variance;

12. Discriminant analysis;

13. Logit choice models.

'The text provides a three-part structure. First, the authors begin each major topic by developing students' statistical intuition through applications. Then, they provide illustrative examples for support. Finally, for those courses where it will be valuable, they describe relevant mathematical underpinnings with vectors and matrix algebra. Additionally, each chapter follows a standard format. This format begins by discussing a general set of research objectives, followed by illustrative examples of problems in different areas. Then it provides an explanation of how each method works, followed by a sample problem, application of the technique, and interpretation of results.

(https://www.cengage.co.in/category/academic-professional/business-economics/operation-decision-science/course/analyzing-multivariate-data-is)