Non-Parametric tests may be, and often are, more powerful in detecting population differences when certain assumptions are not satisfied.
All tests involving ranked data, i.e. data that can be put in order, are non-parametric.
This test can also be applied when the observations in a sample of data are ranks, that is, ordinal data rather than direct measurements. It often involves the use of matched pairs, for example, before and after data, in which case it tests for a median difference of zero. In many applications, this test is used in place of the one sample t-test when the normality assumption is questionable. It is a more powerful alternative to the sign test, but does assume that the population probability distribution is symmetric. This test can also be applied when the observations in a sample of data are ranks, that is, ordinal data rather than direct measurements.