The electroretinogram (ERG) is used to diagnose many kinds of eye diseases. Our final purpose in this paper is a detection of diabetic retinopathy by using only ERG. In this paper, we describe a method to examine whether presented ERG data belong to a group of diabetic retinopathy. The ERG mainly consists of the a-wave, the b-wave and the oscillatory potential (op-wave). It was known that the op-wave varies as progress of retinopathy. Thus, we use the latency, the amplitude and the peak frequency of the op-wave. First, we study these features of sample ERG data, statistically. It was clarified that some of these characteristics are significantly different between a normal group and a group of diabetic retinopathy. By using some of these characteristics, we classify unknown ERG data on the basis of the Mahalanobis' generalized distance or the linear discriminant function. The highest accuracy of this method for the unknown data is about 92.73%.