I need to find the correlation between two data sets that are nonlinear and only have values between 0 and 10. Both sets contained the same number of values.
I've tried using Pearson's R and introducing some linearity by adding n+10 to each data point. That however introduces strong correlation where there really shouldn't be any.
I'm completely new to statistics, so here is a layman's explanation of what I'm trying to achieve.
I have a questionnaire that asks customers for an overall score between 0-10. I then ask several more specific questions for things like Price, Service, etc. These questions are also 0-10.
I want to find the degree of correlation between the overall score and the scores for the specific questions. For example, if customers that give a high score for Price also give a high overall score, then I can see that Price is important to the customer. Whereas if their scores for Service do not closely match the overall score, then the quality of Service is not as important to the customer.
A perfect correlation in my data would look like this:
Price: 10, 10, 10, 10
Overall score: 10, 10, 10, 10
Could someone suggest a suitable coefficient to achieve this?