Quantitative EEG is a sensitive method for measuring pharmacological effects on the central nervous system. Nowadays, computers enable EEG data to be stored and spectral parameters to be computed for signals obtained from a large number of electrode locations. However, the statistical analysis of such vast amounts of EEG data is complicated due to the limited number of subjects usually involved in pharmacological studies. In the present study, data from a trial aimed at comparing diazepam and placebo were used to investigate different properties of EEG mapping data and to compare different methods of data analysis. Both the topography and the temporal changes of EEG activity were investigated using descriptive data analysis, which is based on an inspection of patterns of pd values (descriptive p values) assessed for all pair-wise tests for differences in time or treatment. An empirical measure (tri-mean) for the computation of group maps is suggested, allowing a better description of group effects with skewed data of small samples size. Finally, both the investigation of maps based on principal component analysis and the notion of distance between maps are discussed and applied to the analysis of the data collected under diazepam treatment, exemplifying the evaluation of pharmacodynamic drug effects.