A statistical measure defined as \scriptstyle\operatorname{Cov}(X, Y) = \operatorname{E}((X - \mu) (Y - \nu)) given two real-valued random variables X and Y, with expected values \scriptstyle E(X)\,=\,\mu and \scriptstyle E(Y)\,=\,\nu
A statistical measure used in computing the correlation coefficient between two variables; the covariance is the mean of (x- x(bar))(y-y(bar)) over all pairs of values for the variables x and y, where x(bar) is the mean of the x values and y(bar) is the mean of the y values A statistical value measuring the simultaneous deviations of x and y variables from their means
The sample covariance is a measure of the relationship between the forecasts and observations and is defined as the average of the products of the deviations of each forecast/observation pair from their respective mean
A numerical measure of linear association between two variables Positive values indicate a positive relationship; negative values indicate a negative relationship
Assesses the degree to which two variables co-vary or vary together If the two variables are independent then the covariance will equal zero It is computed as the mean of the products of the mean deviations for each variable
A statistical measure of the correlation between two variables In geostatistics, covariance is usually treated as the simple inverse of the variogram, computed as the overall sample variance minus the variogram value These covariance values, rather than variogram values, are actually used in the Geo-EAS kriging matrix equations for greater computational efficiency
A statistical measure defined as scriptstyleoperatorname{Cov}(X, Y) = operatorname{E}((X - mu) (Y - nu)) given two real-valued random variables X and Y, with expected values scriptstyle E(X),=,mu and scriptstyle E(Y),=,nu
Covariance measures the degree to which two variables move together over time relative to their individual mean returns It is calculated by multiplying the correlation between two variables by the standard deviation for each of the variables = ρ (σx) (σy)
a measure that relates the variances (range or spread) of two sets of values Covariance measures the tendencies of data file values for the same pixel, but in different bands, to vary with each other in relation to the means of their respective bands It is defined as the average product of the differences between the data file values in each band and the mean of each band
average value of the product of deviations of matched pairs of values (of vertical and horizontal wind speeds, for example) from their respective mean values
A statistic used to calculate the correlation coefficient between two variables The covariance is calculated by taking the sum of (x - /x)(y - /x) over all pairs of values for the variables x and y, where /x is the mean of the x values and /y is the mean of all y values
A measure of the degree to which returns on two assets move in tandem A positive covariance means that asset returns move together; a negative covariance means they vary inversely
The covariance is similar to the correlation coefficient in that it measures the relationship between a pair of variables However, unlike the correaltion coefficient it is understandardised in a correlation coefficient the covariance is divided by the standard deviations of x and y