In this question on stackoverflow, I asked about how it is possible to find the individual significance of each correlation coefficient of each node. I answered the question myself later stating that we can use the normalized values of the product of the variables to identify the individual significance. However, I am not sure now whether this is correct or not. The summation that leads to the final correlation coefficient depends on the single values of the product of the normalized x and y. Some of the single values are higher than others which leads to the individual significance.
The reason why I am asking about this because the data are indexed based on the nodes as shown in the table. So I am assuming that the data of each node can have its own effect. For example, all the nodes are contributing to the positive correlation, but node 242 was the reason the correlation coefficient was not 1 but 0.9. So, knowing this, I can isolate and investigate node 242.
nodes closeness degree actual_relays 238 0.622695 0.394077 0.0799 242 0.654735 0.472665 0.0791 247 0.653274 0.476082 0.0673 250 0.648928 0.458998 0.0689 254 0.705788 0.583144 0.1056 259 0.660647 0.486333 0.1125
My background in statistics is mediocre so please correct me as well. Is the method described viable mathematically? If not, then what is the way to go about it? Any references are appreciated.