Pearson Correlation Coefficient

r = Σ(xᵢ−x̄)(yᵢ−ȳ) / √(Σ(xᵢ−x̄)² Σ(yᵢ−ȳ)²). Linear correlation [−1, 1].

Inputs

Result

Pearson r
0.991117
Very strong positive correlation (r² = 0.9823).
  • n pairs6
  • 3.5000
  • ȳ7.0000
  • Σ(x−x̄)(y−ȳ)38.0000
  • Σ(x−x̄)²17.5000
  • Σ(y−ȳ)²84.0000
  • r (Pearson)0.991117
  • r² (variance explained)0.982313
  • Regression slope2.1714
  • Regression intercept-0.6000
  • StrengthVery strong

Step-by-step

  1. Means: x̄ = 3.500, ȳ = 7.000.
  2. Numerator = Σ(x−x̄)(y−ȳ) = 38.000.
  3. Denominator = √(17.500 × 84.000) = 38.341.
  4. r = 38.000 / 38.341 = 0.991117.

How to use this calculator

  • Enter paired x and y values, comma-separated.
  • Calculator pairs them in order.
  • Read r, r², and regression line.

About this calculator

Pearson r measures linear correlation between two variables: r = +1 (perfect positive), 0 (none), −1 (perfect negative). r² = "coefficient of determination" — fraction of variance in y explained by linear relationship with x. Pearson assumes linear, normally-distributed data. For non-linear or rank-based associations, use Spearman ρ. Correlation does not imply causation — always.

Frequently asked

r is the correlation; r² is "% variance explained". r = 0.7 means r² = 0.49 — only 49% explained even with strong correlation.

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