  In this paper we aim to demonstrate how physical perspective enriches usual
statistical analysis when dealing with a complex system of many interacting
agents of non-physical origin. To this end, we discuss analysis of urban public
transportation networks viewed as complex systems. In such studies, a
multi-disciplinary approach is applied by integrating methods in both data
processing and statistical physics to investigate the correlation between
public transportation network topological features and their operational
stability. The studies incorporate concepts of coarse graining and
clusterization, universality and scaling, stability and percolation behavior,
diffusion and fractal analysis.
