In order to have correlation defined, you must understand that is a comparison. A comparison between two distributions, lines or curves. The comparison will tell you how alike or not alike they are.
The sample correlation coefficient, r has a range of -1 to 1. In general, the meaning is:
1 Perfect correlation. They are identical. All data points are on the
line.
0 No correlation. The datasets are not related or correlated.
-1 Perfect negative correlation. They are statistical opposites. All data
points are on the line.
Of course there are all decimal points between these numbers. You are basically looking for an r greater than .7 to say that you have a high correlation between the 2 entities.
The sample correlation coefficient is obtained using this equation:
If you go to Simple Regression Calculation, you can see how correlation is used. In this case, it tells you how well the regression line fits the data from which it is derived.
With correlation defined, you have discovered that it is for comparison. It provides a measure of how well similar sets of data are related to each other.