A unified treatment of the theory and practice of factor analysis and latent variables models. Offers a review of some of the less accessible material on multivariate sampling, measurement and information theory, latent roots and vectors in both real and complex domains. Describes the classical principal components model and sample-population inference. Covers the use of factor models in conjunction with various types of data such as time series, rank orders, nominal variables and directional data. Includes a significant amount of illustrations and exercises.