Abstract: Empirical statistics of the waiting time distributions and the travel distance distributions of 230 residents in an European city for a six-week period is presented. On the hypothesis that the waiting time distributions and the travel distance distributions are power-law at both population and individual levels, the maximum likelihood method is used to estimate the parameters of the distributions. And then the Kolmogorov-Smirnov method is used to test the hypothesises. The results show that the waiting time distributions, neither at population level nor at individual level, are power-law. The probability of that an individual staying at a location for a long time is larger than the prediction of the power-law distribution. The results also show that the travel distance distribution of human can be fitted with a truncated power-law at population level. Yet, at individual level, 198 users have peaked travel distance distributions, peaking at the distance between his or her two most visited locations. The mechanisms of these statistical characteristics are explained.