Since a few days I do not get ahead when trying to compare two Pearson correlation coefficients. Imagine that I've got two datasets where on each I do a correlation between Land Surface Temperature and an urban metric. The datasets are different in their length, so the first one has round about 160.000 observables and the second one has about 2400 observables. For the correlation on the first dataset I get a Pearson of -0.74 and for the second I get -0.885. Now I want to find out whether these coefficients are significantly different from each other. Is there any appropriate method you could suggest?
I already played around with the Fisher-Z-Transformation, but from my point of view with no purposeful results. When I calculate the Fisher-Z on my coefficients, it results in 20.95 (Fisher-Z).
I would be very happy about suitable advices.