Numerous studies have reported long-tailed distributions for various network metrics, including file sizes, transfer times, and burst lengths. We review techniques for identifying long-tailed distributions based on a sample, propose a new technique, and apply these methods to datasets used in previous reports. We find that the evidence for long tails is inconsistent, and that lognormal and other non-long-tailed models are usually sufficient to characterize network metrics. We discuss the implications of this result for current explanations of self-similarity in network traffic.