Covariance and correlation are two concepts in the field of probability and statistics. Both difference between correlation and regression pdf describe the relationship between two variables.
Additionally, both are tools of measurement of a certain kind of dependence between variables. To simplify, a covariance tries to look into and measure how much variables change together. In this concept, both variables can change in the same way without indicating any relationship. Covariance is a measurement of strength or weakness of correlation between two or more sets of random variables, while correlation serves as a scaled version of a covariance. Both covariance and correlation have distinctive types. On the other hand, correlation has three categories: positive, negative, or zero.
Both covariance and correlation have ranges. In terms of covariance, values can exceed or can be outside of the correlation range. Another notable difference is that a correlation is dimensionless. In contrast, a covariance is described in units formed by multiplying the unit of one variable by another unit of another variable.