  The median statistic has recently been discussed by Gott \textit{et al.} as a
more reliable alternative to the standard $\chi^2$ likelihood analysis, in the
sense of requiring fewer assumptions about the data and being almost as
constraining. We apply this statistic to the currently available combined
dataset of 92 distant type Ia supernovae, and also to a mock SNAP-class
dataset. We find that the performances of the modified median and $\chi^2$
statistics are comparable, particularly in the latter case. We further extend
the work of Gott \textit{et al.} by modifying the median statistic to account
for the number and size of sequences of consecutive points above or below the
median. We also comment on how the performance of the statistic depends on the
choice of free parameters that one is estimating.
