  Any simulation of the r-process is affected by uncertainties in our present
knowledge of nuclear physics quantities and astrophysical conditions. It is
common to quantify the impact of these uncertainties through a global
sensitivity metric, which is then used to identify specific nuclides that would
be most worthwhile to measure experimentally. Using descriptive statistics, we
assess a set of metrics used in previous sensitivity studies, as well as a new
logarithmic measure. For certain neutron-rich nuclides lying near the r-process
path for the typical hot-wind scenario, we find opposing conclusions on their
relative sensitivity implied by different metrics, although they all generally
agree which ones are the most sensitive nuclei. The underlying reason is that
sensitivity metrics which simply sum over variations in the r-process
distribution depend on the scaling used in the baseline, which often varies
between simulations. We show that normalization of the abundances causes
changes in the reported sensitivity factors and recommend reporting a minimized
F statistic in addition to a scale estimation for rough calibration to be used
when comparing tables of sensitivity factors from different studies.
