I am unable to understand the practical use of Covariance and Variance.
In my understanding, Covariance and Correlation are both measures of how one variable changes with respect to another. The only difference I see is that Correlation is scaled down to [-1, 1]
I understand the individual differences between Covariance/Correlation and Variance/Standard Deviation. The reason I have grouped these 4 together in this question is the common phrase scaled down. I am learning computer vision programming and I was wondering why would I ever use something which is not bounded (like covariance). Similarly, Standard Deviation will give a smaller range than variance to process data.