In probability theory and statistics, the mathematical concepts of covariance and correlation are very similar. Both describe the degree to which two...

that are in common for the two random variables. The correlation coefficient normalizes the covariance by dividing by the geometric mean of the total variances...

correlation coefficient Cophenetic correlation Correlation disattenuation Correlation function Correlation gap Covariance Covariance and correlation Cross-correlation...

statistics, canonical-correlation analysis (CCA), also called canonical variates analysis, is a way of inferring information from cross-covariance matrices. If...

theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix)...

In statistics and in probability theory, distance correlation or distance covariance is a measure of dependence between two paired random vectors of arbitrary...

partial correlations can be challenging. In this scenario, the sample covariance Σ ^ {\displaystyle {\hat {\Sigma }}} is not well-conditioned, and finding...

has a value between −1 and 1. As with covariance itself, the measure can only reflect a linear correlation of variables, and ignores many other types...

Correlation does not imply causation Covariance function Pearson product-moment correlation coefficient Correlation function (astronomy) Correlation function...

Convolution Correlation Correlation function Cross-correlation matrix Cross-covariance Cross-spectrum Digital image correlation Phase correlation Scaled correlation...

exponential and squared exponential covariance functions as special cases. Autocorrelation function Correlation function Covariance matrix Covariance operator –...

In statistics, the interclass correlation (or interclass correlation coefficient) measures the relationship between two variables of different classes...

The phrase "correlation does not imply causation" refers to the inability to legitimately deduce a cause-and-effect relationship between two events or...

mechanics, the correlation function is a measure of the order in a system, as characterized by a mathematical correlation function. Correlation functions describe...

Autocorrelation, sometimes known as serial correlation in the discrete time case, measures the correlation of a signal with a delayed copy of itself....

In statistics, and especially in biostatistics, cophenetic correlation (more precisely, the cophenetic correlation coefficient) is a measure of how faithfully...

The eddy covariance (also known as eddy correlation and eddy flux) is a key atmospheric measurement technique to measure and calculate vertical turbulent...

In statistics, Spearman's rank correlation coefficient or Spearman's ρ is a number ranging from -1 to 1 that indicates how strongly two sets of ranks...

In probability theory and in particular in information theory, total correlation (Watanabe 1960) is one of several generalizations of the mutual information...

In probability theory and statistics, a cross-covariance matrix is a matrix whose element in the i, j position is the covariance between the i-th element...

remaining element is known. Exchangeable sequences have some basic covariance and correlation properties which mean that they are generally positively correlated...

individual's genotype. Gene–environment correlations (or rGE) is correlation of two traits, e.g. height and weight, which would mean that when one changes...

same level have covariance $\sigma^2$?, URL (version: 2016-03-22) link Stanish W, Taylor N (1983). "Estimation of the Intraclass Correlation Coefficient for...

also related to canonical correlation analysis (CCA). CCA defines coordinate systems that optimally describe the cross-covariance between two datasets while...

In probability theory and statistics, given a stochastic process, the autocovariance is a function that gives the covariance of the process with itself...

( 0 , t ) . {\displaystyle W_{t}=W_{t}-W_{0}\sim N(0,t).} The covariance and correlation (where s ≤ t {\displaystyle s\leq t} ): cov ⁡ ( W s , W t ) =...

covariance, also called the Matérn kernel, is a covariance function used in spatial statistics, geostatistics, machine learning, image analysis, and other...

In statistics, polychoric correlation is a technique for estimating the correlation between two hypothesised normally distributed continuous latent variables...

In statistics, the concordance correlation coefficient measures the agreement between two variables, e.g., to evaluate reproducibility or for inter-rater...

(sample average) or empirical mean (empirical average), and the sample covariance or empirical covariance are statistics computed from a sample of data on one...