I study nanoparticles. Basically, they are prepared by being "etched away" from larger chunks of material. I need to describe their sizes, i.e. fit the histogram of measured sizes, with a probability distribution. The measured distribution is clearly asymmetrical with a tail toward larger sizes (see the attached picture, histograms with much higher numbers of occurrences have basically the same shape). (i) Which probability distribution is suitable for the description of these data? When trying to fit the data using common distributions (Gauss/Lorentz clearly don't fit very well, lognormal), Poisson seems to be the best match (just judging from the shape). (ii) Should the distribution be discrete or continuous? At such small sizes (4 nm) the crystal lattice constant (0.54 nm) becomes significant (i.e. approx. 8 crystal lattices per particle), but the size is also influenced by the rearrangement of atoms at the surface and the surface termination. So, the size is not just "integer multiple" of the crystal lattice constant.