Normalized additional velocity distribution: a fast sample analysis for
  dark matter or modified gravity models
  Here we propose a fast and complementary approach to study galaxy rotation
curves directly from the sample data, instead of first performing individual
rotation curve fits. The method is based on a dimensionless difference between
the observational rotation curve and the expected one from the baryonic matter
($\delta V^2$). It is named as Normalized Additional Velocity (NAV). Using 153
galaxies from the SPARC galaxy sample, we find the observational distribution
of $\delta V^2$. This result is used to compare with the model-inferred
distributions of the same quantity. We consider the following five models to
illustrate the method, which include a dark matter model and four modified
gravity models: Burkert profile, MOND, Palatini $f(R)$ gravity,
Eddington-inspired-Born-Infeld (EiBI) and general relativity with
renormalization group effects (RGGR). We find that the Burkert profile, MOND
and RGGR have reasonable agreement with the observational data, the Burkert
profile being the best model. The method also singles out specific difficulties
of each one of these models. Such indications can be useful for future
phenomenological improvements. The NAV method is sufficient to indicate that
Palatini $f(R)$ and EiBI gravities cannot be used to replace dark matter in
galaxies, since their results are in strong tension with the observational data
sample.
