I have two sets of numbers, that represent grades from two different groups of students, A and B, these grades go from 0 up to 1000. These sets have very different distributions, while set A has a lot of lower values (e.g. 220,270,300,...) set B has a lot of higher values (e.g. 620, 700, 800). Thus, a grade of 650 from a student of group A would be considered extremely high since not many students have a grade so high as that, however, that same grade in set B would be considered a low grade.
Therefore, I want to find a way to put these datasets on the same scale (or rescale one of them) so that I can make comparisons between them, comparisons that take into account the distribution of the grades.
This, way a score of 650 in A, which is considered extremely high, would be equivalent in the set B to 950 which is also an extremely high grade in B, for example.
I tried to normalize and use the z-score, but nothing seems to make sense.
PS: the numeric values are just illustrative.