The nonparametric tests discussed in your book (Wilcoxon rank sum test,sign test,Wilcoxon signed rank sum test,Kruskal-Wallis test,and Friedman test) all require that the probability distributions be:

A) identical except with respect to shape (distribution) .
B) identical except with respect to spread (variance) .
C) identical except with respect to location.
D) different with respect to location,spread,and shape.

Nonparametric tests assume that the probability distributions are identical except with respect to location, meaning that the distributions have the same shape and spread, but may be shifted (or scaled in the case of the Wilcoxon signed rank test) relative to each other. Nonparametric tests are used when the assumptions of parametric tests (such as normal distribution and homogeneity of variance) are not met, and they do not require specifying a particular distribution or estimating parameters.