Both correlation and covariance are an indicator of the relationship between two variables. They indicate whether the variables are positively or negatively related.

The correlation also indicates the degree to which the two variables are related. It's a translation of covariance into a unit-less measure that we can understand (-1.0 to 1.0). The correlation of the variable with itself is always 1.

This video takes an example to explain the two concepts:

This video is developed by David from Bionic Turtle.