Pearson and Spearman Correlation Calculator
Measure paired linear or rank association with explicit average ranks for ties.
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How to use Pearson and Spearman Correlation Calculator
Pearson correlation normalizes centered cross-products. Spearman first replaces each list with average ranks of tied values, then applies Pearson arithmetic.
- Enter paired x observations, paired y observations.
- Check the model, units, and supported limits before calculating.
- Run the tool, inspect the result, then copy or download it.
Good to know
- 3–1000 matched pairs and nonconstant lists. Compensated centered sums reduce cancellation. No p value, independence guarantee, causal inference, or extrapolation.
- Runs locally. Numeric inputs are bounded; floating-point output is approximate and rounded to 12 significant digits. Unsupported or non-finite calculations produce an error.
Common questions
How does Pearson and Spearman Correlation Calculator calculate its result?
Pearson correlation normalizes centered cross-products. Spearman first replaces each list with average ranks of tied values, then applies Pearson arithmetic.
What assumptions and boundaries apply?
3–1000 matched pairs and nonconstant lists. Compensated centered sums reduce cancellation. No p value, independence guarantee, causal inference, or extrapolation.
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