We carried out a number of some experiments and got 10 independent 2-samples datasets.
Is it possible to show a significant difference between the two samples, if each of them contains more than 75% zeros (and we don't want to exclude zeros from these samples)?
Example of sample's box plots obtained by one of our experiments below:
It is important to note that in 10 independent models (experiments) the difference is approximately the same visually, but Kolmogorov-Smirnov, Brunner-Munzel and Wilcoxon tests show unstable p-values for different models.
What statistical test should we use to show the significance of differences in these cases? Or zero-values filtering is necessary?