Through analyzing the real data of bank customers visiting in a bank outlet in 19 days,it was discovered that there were many forms of nonPoisson characters appearing in the data of bank customers visiting,such as interarrival time distribution of all customers in 19 days,total customers visiting in one day,customers visiting for personal banking business in 19 days and customers visiting for corporate banking business in 19 days.These characters were different from those in the hypothesis of queuing theory:the coming of customers could be well approximated by Poisson processes.These distributions denoted the pattern of bank customers visiting follows nonPoisson statistics or heavy tailed distribution.It is found that most of these distribution exponents are between 2 and 3.This result establishes the empirical foundation of new queuing theory with powerlaw interarrival time distribution,and also explores the analysis of bank queuing in further studies.