  Friedman test is a nonparametric method that proposed for analyzing data from
a randomized complete block design as a robust alternative to parametric method
and widely applied in many fields such as agriculture, biology, business,
education, and medicine. After the null hypothesis of no treatment effects is
rejected, the post-hoc pairwise comparisons must be applied to identify where
the differences occur. As the number of groups increases, the number of
required comparisons becomes large and this may increase the type I error. The
aim of this study is twofold. The main aim is to suggest expression that
facilitates the plotting Friedman test by gathering the test and pairwise
comparisons in one simple step. The second aim is to derive the sampling
distribution of the suggested expression by utilizing method of moments that
helps in obtaining the decision limit. An application and simulation study are
carried out to show the advantage of the suggested method and to compute the
empirical type I error. The results are of great value where the proposed
method makes huge reduction in the number of required tests to show where the
discrepancies occur, holds the type I error close to the nominal value and
provides visual, deep insight and understanding where the treatment effects
occur.
