I have a program which produces an image, and I use a metric to understand how accurate that image is. I choose five cases (A, B, C, D, E), and make a list of the accuracy metric for each case:
program_metrics = [0.1, 0.3, 0.2, 0.1, 0.5]
This list is ordered by case, i.e. A's accuracy is 0.1, B's accuracy is 0.2, etc.
I then take these images, and ask some experts to provide a metric between 0 and 1 to determine how accurate these five cases are. I make a list of the expert's metrics:
expert_metrics = [0.3, 0.5, 0.1, 0.5, 0.2]
This list is also ordered by case, i.e. the experts consider A's accuracy to be 0.3, B's accuracy to be 0.5, etc.
I would like to have a metric to measure how correlated these two sets of data are, taking into account the pairs of data, which metric could I use? Would the Pearson Correlation Coefficient be of use here?
I want to determine whether there is some sort of similarity between the program's metrics and the experts' metrics.