Abstract As in other areas of geophysics or meteorology, the observations and data collected at volcanoes are the result of experiments in which we cannot control the variables we wish to study. Thus, statistical analysis is an extremely important step in the data processing. Variations in the experimental parameters must be controlled through the choice of samples and through the hypotheses chosen for testing. The evaluation of the samples is possible only through the application of the proper statistical methods, especially multivariate statistics. Volcanic activity is the manifestation of complex dynamic processes and interactions within the volcano. It dependson the movement of fluids as well as on the thermodynamics of the magma and gases within a branched network of conduits and cavities. The dynamic processes generate various geophysical signals, as well as visible phenomena at the volcano’s surface. State-of-the-art techniques for monitoring at volcanoes now include continuous and concurrent recording of a variety of both quantitative and qualitative observations using a multi-parameter station in the near-field of thecrater. Such a station has been installed at Galeras volcano in Colombia, and has been operating for several years ( Seidl et al. 2003 ). Presumably, the signals and phenomena observed at the surface of a volcano have acommon source in terms of the strong interactions between various internal processes. Thus, data from different measurements should show a significant correlation. Contingency tables are a powerful statistical method for investigating such multi-dimensional correlations between quantitative and qualitative data. The pattern of signals and phenomena, aswell