Seems likely. The presented coefficient only looks at the ordering of the X-values, and how it relates to the ordering of the Y-values. All other information is thrown away. That's how it can be so general, but it should come at the expense of power.
Seems likely. The presented coefficient only looks at the ordering of the X-values, and how it relates to the ordering of the Y-values. All other information is thrown away. That's how it can be so general, but it should come at the expense of power.
Ah that makes sense intuitively. I was confused how non linear correlation could be detected without knowing anything about the function itself.
power and interpretability.
Assuming a linear relationship, if you know the correlation coefficient, you can predict unobserved values of y based on a known x with good accuracy.
y = ax + b + error
where strong correlation means error is small.