Review of Twenty Nonparametric Statistics and Their Large Sample Approximations.

By Gail F. Fahoome, Shlomo S. Sawilowsky. 2000

49 citations recorded by the source corpus.

Nonparametric procedures are often more powerful than classical tests for real world data, which are rarely normally distributed. However, there are difficulties in using these tests. Computational formulas are scattered tnrous-hout the literature, and there is a lack of avalialalicy of tables of critical values. This paper brings together the computational formulas for 20 commonly used nonparametric tests that have large-sample approximations for the critical value. Because there is no generally agreed upon lower limit for the sample size, Monte Carlo methods have been used to determine the smallest sample size that can be used with the large-sample approximations. The statistics reviewed include single-population tests, comparisons of two populations, comparisons of several populations, and tests of association. (Contains 4 tables and 59 references.) (Author/SLD) Reproductions supplied by EDRS are the best that can be made from the original document. Review of Twenty Nonparametric Statistics and Their Large Sample Approximations

Subfields: Education, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f5cf5945c5f2d652b9e2c803b8ea31ca02abe0b4