ABSTRACT
Many of the models discussed in this book are based on the assumption that the perceptual effect of a stimulus is random over trials, although on any single trial is has a specified fixed value. This assumption, which can be traced back to Fechner (1860, 1966), was fully exploited in signal detection theory (e.g., Green & Swets, 1974) where the focus was on unidimensional perceptual representations. The models in this book focus on multidimensional representations. Although the mathematical basis of these models is probability theory, the generalization from univariate to multivariate probability distributions involves several complications. This first chapter reviews many of the important results of multivariate probability theory upon which the later chapters depend.
