A new methodology for assessing distributional assumptions of multivariate data, with graphical applications, is developed. The underlying procedure is based on transforming the multivariate sample into a set of uncorrelated samples and representing the order statistics of each transformed sample by linked vectors in a two dimensional space. The multivariate normality tests are reviewed in detail, the proposed method is described and its properties are discussed.