Correlation Calculator
Enter two equally sized data sets to calculate the Pearson correlation coefficient (r) and measure their linear relationship.
How to Use the Correlation Calculator
Enter paired X and Y values to calculate the strength and direction of their linear relationship.
Practical Example
If larger X values consistently occur with larger Y values, the correlation coefficient can approach +1.
Factors That Affect the Result
Outliers, non-linear relationships, sample size and data quality can strongly affect correlation.
Frequently Asked Questions
What does r = 1 mean?
It indicates a perfect positive linear relationship.
Does correlation prove causation?
No.
Can a strong non-linear relationship have low Pearson correlation?
Yes, because Pearson correlation focuses on linear association.
Interpreting Correlation
Correlation measures the strength and direction of a relationship between two variables. Pearson's correlation coefficient ranges from −1 to +1. Values near +1 indicate a strong positive linear relationship, values near −1 indicate a strong negative linear relationship, and values near zero indicate little linear association. For example, if two measurements tend to rise together, their correlation may be positive. Correlation does not prove that one variable causes the other, and a strong nonlinear relationship can still have a low Pearson coefficient. Outliers can also change the result substantially. When using correlation, inspect the underlying data and, when possible, a scatter plot rather than relying on the coefficient alone. The variables should be paired correctly so each x value corresponds to the appropriate y value.