Summary
A statistical analysis using the forward search produces many graphs. For multivariate data an appreciable proportion of these are a variety of plots of the Mahalanobis distances of the individual observations during the search. Each unit, originally a point in v-dimensional space, is then represented by a curve in two dimensions connecting the almost n values of the distance for each unit calculated during the search. Our task is now to recognise and classify these curves: we may find several clusters of data, or outliers or some unexpected, non-normal, structure. We look at the plots from five data sets. Statistical techniques include cluster analysis and transformations to multivariate normality.