Correlation Coefficient Calculator
Find the Pearson correlation coefficient between two datasets.
Assumptions used in this calculation
- Linear relationships only: Pearson's r only detects linear association; two variables with a strong non-linear (e.g. curved) relationship can still produce an r close to 0.
About this calculator
Eyeballing a scatter plot can suggest two variables move together, but putting a number on how strongly and in what direction requires Pearson's correlation coefficient, and its formula involves several running sums across paired data that are impractical to track by hand for anything beyond a handful of points. This calculator takes two paired sets of x and y values and computes r = (nΣxy − ΣxΣy) ÷ √[(nΣx² − (Σx)²)(nΣy² − (Σy)²)], which always falls between −1 and 1: values near 1 indicate a strong positive linear relationship, near −1 a strong negative one, and near 0 little to no linear relationship. It measures linear association specifically, so a strong non-linear (e.g. curved) relationship between two variables can still produce an r close to 0, and a high r never by itself establishes that one variable causes the other. That gives a precise, comparable measure of linear relationship strength instead of a subjective read of a scatter plot.
Worked example
5 data points
Result: r = 0.7746 (strong positive)
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