Difference between covariance and correlation??

Thank you for replying. Actually I got this one but could you please elaborate a bit on it. I am keen to know the practical implications of both.

Yes. Sure. So basically, covariance will tell us whether the variables are positively related or negatively related. That is, the covariance value can be negative or positive; if the value is positive that means X and Y are directly related. Both increase and decrease together. But if covariance value is negative, that will mean X and Y are inversely related. When one increases, other decreases and vice versa. So covariance can tell us what is the direction in which X and Y are related.

But correlation has an added advantage. It not only tell us the direction of linear relationship, it also tell us the strength. Correlation value is standardized, in the sense that it can be any value equal to or greater than -1 and equal to or lesser than +1. A correlation of -1 or +1 indicates X and Y are 100% related. Their relationship is completely proportional. A correlation of 0 shows no linear relationship. So as the absolute value of correlation increases, the strength of linear relationship increases. This is how correlation is an advantage above covariance.

Let me know if this is clear.

Absolutely clear 😊 Thank you so much!!