Elements in a sample date are demonstrated based on their characteristics and in turn the characteristics are represented by variables. Identifying the relationship between these variables is crucial for prediction, hypothesis testing, and decision making. The relation between two variables is often quantified using a correlation factor. Once correlation is known it can be used to make predicti...

The Pearson correlation coefficient based on the customer relationship clearly illustrate to the product development process. It developed in an association from the customer relationship management process. The CRM should be implemented to the Pearson correlation algorithm. In an existing system is used to implement for a customer association management in an organization process implement for...

In statistics, the Pearson correlation coefficient rx,y determines the degree of linear correlation between two variables and it is known that −1 ≤ rx,y ≤ 1. In the theory of networks, a curious expression proposed in [PRL 89 208701 (2002)] for degree-degree correlation coefficient rji,ki , i ∈ [1,M ] has been in use. We realize that the suggested form is the conventional Pearson’s coefficient ...

This paper introduces a causation coefficient which is defined in terms of probabilistic causal models. This coefficient is suggested as the natural causal analogue of the Pearson correlation coefficient and permits comparing causation and correlation to each other in a simple, yet rigorous manner. Together, these coefficients provide a natural way to classify the possible correlation/causation...