# R2 (correlation coefficient)

The most familiar measure of dependence between two quantities is the Pearson product-moment correlation coefficient, or "Pearson's correlation coefficient", commonly called simply "the correlation coefficient". The correlation coefficient is a statistical measure of the strength of the relationship between the relative movements of your two variables. The values range between -1.0 and 1.0. A calculated number less than -1.0 or greater than 1.0 means that there was an error in the measurement. A correlation of -1.0 shows a perfect correlation but negative, while a correlation with 1.0 value shows a perfect correlation in positive. A correlation with 0.0 value shows no relationship between the movement of your two variables. The correlation coefficient is widely used in all category of sciences. The correlation coefficient was developed by Karl Pearson from a related idea introduced by Francis Galton in the 1880s and for which the mathematical formula was derived and published by Auguste Bravais in 1844. Pearson's correlation coefficient is R but R2 is squared of Pearson's correlation coefficient.

- r = The Correlation coefficient
- n = number in the given dataset
- x = first variable in the context
- y = second variable

Paste 2-columns data here (obs vs. sim). In format of excel, text, etc. Separate it with space:

Correlation Coefficient (R2):