Abstract An important question in many parasitological studies is the assessment of differences in parasite numbers between samples of hosts. This is not always easy: while almost everybody will agree that the main task consists in deciding whether the values in one sample tend to be higher than the values of the other sample, there is considerable disagreement about what higher (or lower) should mean. In common use as dissimilarity measures are differences between mean values, medians, geometric means, prevalence rates, relative effects, and more. In general, different measures can lead to different conclusions. However, a debate as to which measure is superior is fruitless; it depends on goals and circumstances of the respective study. In our opinion, it is more important to identify situations in which most of the above mentioned measures coincide, and hence, one can confidently claim that the values in one sample are higher than in the other. This is the case when one sample is stochastically larger than the second. It is the aim of this paper to review this concept using distributional and data examples, and of proposing graphical tools for detecting stochastic dominance
