  The rank correlation coefficients and the ranked-based statistical tests (as
a subset of non-parametric techniques) might be misleading when they are
applied to subjectively collected opinion scores. Those techniques assume that
the data is measured at least at an ordinal level and define a sequence of
scores to represent a tied rank when they have precisely an equal numeric
value.
  In this paper, we show that the definition of tied rank, as mentioned above,
is not suitable for Mean Opinion Scores (MOS) and might be misleading
conclusions of rank-based statistical techniques. Furthermore, we introduce a
method to overcome this issue by transforming the MOS values considering their
$95\%$ Confidence Intervals. The rank correlation coefficients and ranked-based
statistical tests can then be safely applied to the transformed values. We also
provide open-source software packages in different programming languages to
utilize the application of our transformation method in the quality of
experience domain.
