A target transformation factor analysis has been used for the quantitative resolution of environmental data. The initial studies have utilized the correlation between samples as the matrix defining the relationships within the data. The analysis of this matrix is a Q-mode analysis. For large data sets, this technique requires the diagonilization of a large matrix. An alternative approach is to examine the matrix of correlations between the measured parameters. The analysis of this matrix is called an R-mode analysis. It is found that for several typical data sets, equivalent results are obtained for the two modes and, in some cases, R-mode may yield better results. The faster diagonalization and smaller memory requirements of R-mode would seem to make it preferable.