Why do researchers use nonparametric tests? Describe a psychological research situation or scenario that would use a nonparametric test. Why would the nonparametric test be used?

     Nonparametric tests (distribution free tests) are statistical tests, which can be used with data and with skewed distributions at the nominal or ordinal level of measurement (Weaver, 2002). The reason they are also called distribution free tests is because the assumptions underlying their use are weaker and fewer than the assumptions associated with parametric tests (Weaver, 2002). Nonparametric tests barely require any assumptions concerning the shapes of the underlying population distributions (Weaver, 2002). Which is why nonparametric test are used instead of parametric tests if the assumptions of the parametric test have been grossly violated (Weaver, 2002). Nonparametric test are also referred to as rank-order tests because rank or ordinal data usually requires nonparametric analysis. Researchers use nonparametric tests when certain assumptions cannot be made about the population and when the type of data is ordinal in nature and not at least interval. A psychological research situation where the effects of deliberately induced stress on participants could be ranked according to how fast each participant recovers to a normal stress free state (first, second third, and so forth) and ranked on how accurately they perform test right after stress is induced (first, second third, and so forth). 

 Reference

 Weaver, B. (2002). Angelfire. Retrieved from http://www.angelfire.com/wv/bwhomedir/notes/nonpar.pdf