Statistics

Correlation Coefficient Calculator

Quantify the strength and direction of a linear relationship with Pearson’s r plus the supporting covariance and standard deviations.

correlationpearson rcovariance
Correlation Coefficient Calculator

Quantify linear association between paired lists with Pearson r and R².

Pairs processed
4
Pearson r
0.996
0.992
Sample covariance
160.167
Std dev (X)
11.619
Std dev (Y)
13.841

Pearson correlation

r = Σ((x − x̄)(y − ȳ)) / [(n − 1) sₓ sᵧ]

Standard deviations sₓ and sᵧ come from the same datasets, so r stays bounded between −1 and 1 and highlights how tightly the paired values move together.

How to use

  1. Paste X values and Y values in the same order.
  2. Ensure each list has at least two numeric entries.
  3. Review r, R², covariance, and each sample standard deviation.

Example

Input: X = 12, 18, 25, 39; Y = 22, 32, 38, 55

Output: r ≈ 0.99, R² ≈ 0.98, Covariance ≈ 107.8

FAQ & notes

How does this differ from regression?

Correlation measures strength of association only. If you also need slope and predictions, jump to the linear regression calculator.

Why does r sometimes report 0?

If one list has no variation (all values identical) the standard deviation is zero, so Pearson r cannot be computed and the calculator reports 0 as a neutral result.