In this paper, we provide a descriptive statistical analysis of subjective experiments in mobile imaging. Most of the statistical analyses of such experiments use condensed statistics such as mean opinion scores along with standard deviations. These statistics give only limited insights on the underlaying distribution of a data set. On the other hand, higher order statistics such as skewness and kurtosis provide additional information about a distribution but their qualitative interpretation is complicated. In order to alleviate these shortcomings, we advocate the use of box plots to efficiently visualize and compare distributions between different sets of image quality scores. Specifically, box plots serve the purposes of accounting for the diversity in image quality scores as well as supporting an intuitive qualitative interpretation of the results. It is shown by analysing two subjective experiments of the wireless imaging quality database that notched box plots are beneficial in quickly assessing the statistical significance among differences in such experiments. Further, box plots are used to identify those test material that received a wide diversity in image quality scores including outliers.