Correlationaldepends
Correlationaldepends is a concept used in statistics and data analysis to describe a form of dependency among variables that is captured mainly by correlation measures. In this view, pairs or groups of variables exhibit associations that can be summarized by correlation coefficients and by the structure of a correlation matrix, rather than by explicit causal links.
It is not a formal theory on its own, but a descriptive stance: strong correlations indicate a
Common tools to study correlational dependencies include Pearson, Spearman, and Kendall correlations, cross-correlation for time series,
Limitations include sensitivity to outliers, nonlinearity, and spurious correlations arising from sampling or bias. Nonlinear or
Applications of the correlationaldepends perspective appear across fields such as finance, genetics, social sciences, and engineering,
See also: correlation, partial correlation, dependence, copula, causation, conditional independence.