Correlation Coefficient Calculator
Calculate Pearson's correlation coefficient r and r² for paired x, y data. Get a plain-English read of the strength and direction of the linear relationship.
Enter at least 3 x, y pairs (one per line) to compute Pearson's correlation coefficient.
What is the Correlation Coefficient Calculator?
The ByteTools Correlation Coefficient Calculator computes Pearson's r for paired x/y data — the standard measure of how strongly two variables move together linearly.
- Pearson's r from the covariance / standard-deviation formula
- r² (coefficient of determination) included
- Plain-English strength and direction interpretation
- Shows means and intermediate sums Sxx, Syy, Sxy
- Paste-friendly input straight from spreadsheet columns
- 100% private — runs entirely in your browser
How to use the Correlation Coefficient Calculator
- 1
Enter your data as one x, y pair per line (comma, space or tab separated).
- 2
Read Pearson's r and the coefficient of determination r².
- 3
Check the interpretation of strength and direction.
- 4
Review the intermediate sums (Sxx, Syy, Sxy) to verify the working.
- 5
Copy the summary with one click.
About the Correlation Coefficient Calculator
The ByteTools Correlation Coefficient Calculator computes Pearson's r for paired x/y data — the standard measure of how strongly two variables move together linearly. It uses the classic formula: the covariance of x and y divided by the product of their standard deviations, r = Sxy / √(Sxx·Syy).
Alongside r you get r² (the coefficient of determination, the share of variance in y explained by x), the means, and the intermediate sums Sxx, Syy and Sxy so you can follow the calculation. A plain-English interpretation classifies the relationship: strong, moderate or weak, positive or negative.
Paste pairs straight from a spreadsheet — one x, y pair per line. Everything is computed 100% locally in your browser; your data is never uploaded, stored or shared.
Frequently asked questions
How do you calculate the correlation coefficient?
Compute the deviations of each x and y from their means, then r = Σ(x−x̄)(y−ȳ) divided by the square root of Σ(x−x̄)² × Σ(y−ȳ)². For x = 1…5 and y = 2, 4, 5, 4, 5 this gives r = 6/√(10×6) ≈ 0.775, a fairly strong positive correlation.
What does r = 0.7 mean?
An r of 0.7 indicates a fairly strong positive linear relationship: as x rises, y tends to rise. Squaring it, r² = 0.49, meaning about 49% of the variation in y is associated with variation in x. The remaining variation comes from other factors or noise.
What is the difference between r and r²?
r measures the direction and strength of a linear relationship on a scale from −1 to 1. r² is its square, ranging 0 to 1, and states the proportion of variance in one variable explained by the other. r keeps the sign; r² does not.
Does correlation imply causation?
No. A high r shows that two variables move together, not that one causes the other. The link could run either way or be driven by a third variable. Correlation is evidence worth investigating, not proof of cause and effect.
What sample size do I need for a meaningful correlation?
With very few pairs, r is extremely unstable — with n = 3 or 4, large r values arise easily by chance. Most references suggest at least 20–30 pairs before reading much into moderate correlations. This tool requires at least 3 pairs and reports n so you can judge.
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