Dear Rick, I have a bivariate dataset which is classified into two groups - yes and no. I'm trying to determine which group a new observation should belong based on the shorter Mahalanobis distance. The data is univariately normal for both variables but highly correlated (pearson correlation is 0.88) and therefore fails MVN test. The two groups have different means and variance. Is it valid to compare the Mahalanobis distance of the new observation from both groups, in order to assign it to one of the groups? If not, can you please let me know any workaround to classify the new observation? Eg use cholesky transformation