I've seen some similar articles using R but I'm not sure how to implement this test in python.
Suppose I have two datasets, A and B (both contain 35 datapoints), and they predict some time series of C (also 35 datapoints).
A's correlations with C is r=0.27, B's correlation is r=0.34. This suggests that B explains about 4-5% more variance than A. How can I test to see if A and B are significantly different in predicting C?
I'm guessing some kind of bootstrap may work to see in the 5-95% tails of the distributions overlap, but not sure how to do this.