Search results
Results From The WOW.Com Content Network
Mann–Whitney test (also called the Mann–Whitney–Wilcoxon (MWW/MWU), Wilcoxon rank-sum test, or Wilcoxon–Mann–Whitney test) is a nonparametric statistical test of the null hypothesis that, for randomly selected values X and Y from two populations, the probability of X being greater than Y is equal to the probability of Y being greater than X.
Nonparametric statistics is a type of statistical analysis that makes minimal assumptions about the underlying distribution of the data being studied. Often these models are infinite-dimensional, rather than finite dimensional, as is parametric statistics. [1] Nonparametric statistics can be used for descriptive statistics or statistical inference.
The Kruskal–Wallis test by ranks, Kruskal–Wallis test[1] (named after William Kruskal and W. Allen Wallis), or one-way ANOVA on ranks[1] is a non-parametric statistical test for testing whether samples originate from the same distribution. [2][3][4] It is used for comparing two or more independent samples of equal or different sample sizes.
The rank-biserial is the correlation used with the Mann–Whitney U test, a method commonly covered in introductory college courses on statistics. The data for this test consists of two groups; and for each member of the groups, the outcome is ranked for the study as a whole.
In statistical theory, a U-statistic is a class of statistics defined as the average over the application of a given function applied to all tuples of a fixed size. The letter "U" stands for unbiased. In elementary statistics, U-statistics arise naturally in producing minimum-variance unbiased estimators. The theory of U-statistics allows a ...
In statistics, the Hodges–Lehmann estimator is a robust and nonparametric estimator of a population's location parameter. For populations that are symmetric about one median, such as the Gaussian or normal distribution or the Student t -distribution, the Hodges–Lehmann estimator is a consistent and median-unbiased estimate of the population ...
When categorical data has only two possibilities, it is called binary or dichotomous. [ 1 ] Assumptions, parametric and non-parametric: There are two groups of statistical tests, parametric and non-parametric. The choice between these two groups needs to be justified. Parametric tests assume that the data follow a particular distribution ...
Not to be confused with Tau distribution. In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's τ coefficient (after the Greek letter τ, tau), is a statistic used to measure the ordinal association between two measured quantities. A τ test is a non-parametric hypothesis test for statistical dependence ...