Errors of misclassification and their probabilities are studied for classification problems associated with univariate Nelly distribution. The effect of applying the linear discriminant function (LDF) based on normality to Nelly populations are assessed by comparing probability (Optimum) based on the linear discriminant function (LDF) with those based on the likelihood ratio rule (LR) for the Nelly. Both theoretical and empirical results are presented

Keywords : Errors of Misclassification, Nelly Distribution, Linear Discriminant Function, Likelihood Ratio Rate, Error Rate.