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In statistics, a sequence of random variables is homoscedastic (/ ˌ h oʊ m oʊ s k ə ˈ d æ s t ɪ k /) if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance.
That is because Spearman's ρ limits the outlier to the value of its rank. In statistics, Spearman's rank correlation coefficient or Spearman's ρ, named after Charles Spearman [1] and often denoted by the Greek letter (rho) or as , is a nonparametric measure of rank correlation (statistical dependence between the rankings of two variables).
The coefficient is inside the interval [−1, 1] and assumes the value: 1 if the agreement between the two rankings is perfect; the two rankings are the same. 0 if the rankings are completely independent. −1 if the disagreement between the two rankings is perfect; one ranking is the reverse of the other.
In statistics, the Page test for multiple comparisons between ordered correlated variables is the counterpart of Spearman's rank correlation coefficient which summarizes the association of continuous variables. It is also known as Page's trend test or Page's L test. It is a repeated measure trend test.
Rank correlation is a measure of the relationship between the rankings of two variables, or two rankings of the same variable: Spearman's rank correlation coefficient is a measure of how well the relationship between two variables can be described by a monotonic function.
SOFA Statistics is an open-source statistical package. The name stands for S tatistics O pen F or A ll. It has a graphical user interface and can connect directly to MySQL , PostgreSQL , SQLite , MS Access (map), and Microsoft SQL Server .
In statistics, Goodman and Kruskal's gamma is a measure of rank correlation, i.e., the similarity of the orderings of the data when ranked by each of the quantities.It measures the strength of association of the cross tabulated data when both variables are measured at the ordinal level.
In statistics, Bartlett's test, named after Maurice Stevenson Bartlett, [1] is used to test homoscedasticity, that is, if multiple samples are from populations with equal variances. [2] Some statistical tests, such as the analysis of variance, assume that variances are equal across groups or samples, which can be checked with Bartlett's test.