Applied Multivariate Analysis

Like most academic authors, my views are a joint product of my teaching and my research. Needless to say, my views reflect the biases that I have acquired. One way to articulate the rationale (and limitations) of my biases is through the preface of a truly great text of a previous era, Cooley and Lohnes (1971, p. v). They draw a distinction between mathematical statisticians whose intel- lect gave birth to the field of multivariate analysis, such as Hotelling, Bartlett, and Wilks, and those who chose to &quote;concentrate much of their attention on methods of analyzing data in the sciences and of interpreting the results of statistical analysis . . . . (and) . . . who are more interested in the sciences than in mathematics, among other characteristics. &quote; I find the distinction between individuals who are temperamentally &quote;mathe- maticians&quote; (whom philosophy students might call &quote;Platonists&quote;) and &quote;scientists&quote; (&quote;Aristotelians&quote;) useful as long as it is not pushed to the point where one assumes &quote;mathematicians&quote; completely disdain data and &quote;scientists&quote; are never interested in contributing to the mathematical foundations of their discipline. I certainly feel more comfortable attempting to contribute in the &quote;scientist&quote; rather than the &quote;mathematician&quote; role. As a consequence, this book is primarily written for individuals concerned with data analysis. However, as noted in Chapter 1, true expertise demands familiarity with both traditions.