Multivariate-Data-Analysis-7th-Edition.pdf

I - I , 1 - LVS , IS Overview of Multivariate Methods LEARNING OBJECTIVES Upon completing this chapter, you should be able to do the following: ? Explain what multivariate analysis is and when its ppl cation is appropriate. ? Discuss the nature of measurement scales and their relationship to multivariate techniques. ? Understand the nature of measurement erro and its impact on multivariate analysis. ? Determine which multivariate technique is appropriate for a specific research problem. ? Define the specific techniques included in multivariate analysis. ? Discuss the guidelines for applic tion and interpretation of multivariate analyses. ? Understand the six-step appro ch to multivariate model building. CHAPTER PREVIEW This chapter presen a simplified overview of multivariate analysis. It stresses that multivariate analysis methods will nc easingly influence not only the analytical aspects of research but also the design and approach to data collection for decision making and problem solving. Although multivariate tech- niques sh e many characteristics with their univariate and bivariate counterparts, several key differ- ences arise in the transition to a multivariate analysis. To illustrate this transition, this chapter presents a c as ification of multivariate techniques. It then provides general guidelines for the application of these techniques as well as a structured approach to the formulation, estimation, and interpretation of multivariate results. The chapter concludes with a discussion of the databases utilized throughout the text to illustrate application of the techniques. KEY TERMS Before starting the chapter, review the key terms to develop an understanding of the concepts and ter- minology used. Throughout the ch