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...

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

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

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...

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...

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...

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

theory, the law of total covariance, covariance decomposition formula, or conditional covariance formula states that if X, Y, and Z are random variables...

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

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

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

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

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

inverse problem by simply replacing the objective function by covariance in place of correlation in (2). FSCA aims to quantify the dependency of X , Y {\displaystyle...

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

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

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

( 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 ) =...

_{X}(t_{1})\mu _{Y}(t_{2}).\,} Cross-covariance is related to the more commonly used cross-correlation of the processes in question. In the case...

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

the average short-term correlation. If the signals have multiple components (slow and fast), scaled coefficient of correlation can be computed only for...

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

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

The item–total correlation is the correlation between a scored item and the total test score. It is an item statistic used in psychometric analysis to...

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