Introduction to Multivariate Analysis

Abstract

Multivariate analysis is the more-or-less natural extension of elementary inferential statistics to the case of multidimensional data. The first difficulty the person encounters is the representation of data. How can he visualize data in multiple dimensions, on the basis of our limited ability to plot bidimensional and tridimensional diagrams? This chapter shows that this is just one of the many issues that he may have to face. The richness of problems and applications of multivariate analysis has given rise to a correspondingly rich array of methods. The chapter offers a more general classification. The mathematics involved in multivariate analysis is certainly not easier than that involved in univariate inferential statistics. Finally, the chapter illustrates the important role of linear algebra and matrix theory in multivariate methods. Controlled Vocabulary Terms canonical correlation; cluster analysis; correspondence analysis; covariance matrix; discriminant analysis; factor analysis; inferential statistics; multivariate statistics; principal components analysis

Locations

• Library Union Catalog of Bavaria, Berlin and Brandenburg (B3Kat Repository) - View - PDF