Non-parametric Statistics - Methods

Methods

Non-parametric (or distribution-free) inferential statistical methods are mathematical procedures for statistical hypothesis testing which, unlike parametric statistics, make no assumptions about the probability distributions of the variables being assessed. The most frequently used tests include

  • Anderson–Darling test
  • Statistical Bootstrap Methods
  • Cochran's Q
  • Cohen's kappa
  • Friedman two-way analysis of variance by ranks
  • Kaplan–Meier
  • Kendall's tau
  • Kendall's W
  • Kolmogorov–Smirnov test
  • Kruskal-Wallis one-way analysis of variance by ranks
  • Kuiper's test
  • Logrank Test
  • Mann–Whitney U or Wilcoxon rank sum test
  • McNemar's test
  • median test
  • Pitman's permutation test
  • Rank products
  • Siegel–Tukey test
  • Spearman's rank correlation coefficient
  • Wald–Wolfowitz runs test
  • Wilcoxon signed-rank test.

Read more about this topic:  Non-parametric Statistics

Famous quotes containing the word methods:

    In inner-party politics, these methods lead, as we shall yet see, to this: the party organization substitutes itself for the party, the central committee substitutes itself for the organization, and, finally, a “dictator” substitutes himself for the central committee.
    Leon Trotsky (1879–1940)

    Parents ought, through their own behavior and the values by which they live, to provide direction for their children. But they need to rid themselves of the idea that there are surefire methods which, when well applied, will produce certain predictable results. Whatever we do with and for our children ought to flow from our understanding of and our feelings for the particular situation and the relation we wish to exist between us and our child.
    Bruno Bettelheim (20th century)

    The philosopher is in advance of his age even in the outward form of his life. He is not fed, sheltered, clothed, warmed, like his contemporaries. How can a man be a philosopher and not maintain his vital heat by better methods than other men?
    Henry David Thoreau (1817–1862)