Meanings of the Word “Nonparametric”
The terminology nonparametric was introduced by Wolfowitz in 1942 to encompass a group of statistical techniques for situations where one does not specify the functional form of the distributions of the random variables that one is dealing with. In its earlier form, this comprised mainly methods working with rank statistics, and was also coined “distribution free” methods. Most often these methods are applied to perform hypothesis tests. For an example of such a hypothesis test, see the entry by Jurec̆ková (same volume). Other examples include the Kolmogorov–Smirnov test, the runs test, sign test, Wilcoxon-signed-rank test, the Mann–Whitney \(U\)-test (see WilcoxonMannWhitney Test) and Fisher Exact Test. For an overview and details, see Hollander (1999). This type of nonparametric method has the advantage that it can be applied to ordinal and rank data; the data may be frequencies or counts, and do not have to be measured on a continuous scale.
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References and Further Reading
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Jansen, M., Claeskens, G. (2011). Nonparametric Estimation. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_414
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