Both covariance and correlation measure the relationship and the dependency between two variables.
Covariance indicates the direction of the linear relationship between variables.
Correlation measures both the strength and direction of the linear relationship between two variables.
Correlation values are standardized.
Covariance values are not standardized.
While correlation coefficients lie between \(-1\) and \(+1\), covariance can take any value between \(-\infty\) and \(+\infty\).
Correlation is dimensionless. It's a unit-free measure of the relationship between variables. This is because we divide the value of covariance by the product of standard deviations which have the same units.