The calculation, without hidden assumptions
Correlation measures association, not causation. Pearson r measures linear association in the original values; Spearman rho applies the same correlation calculation to ranks and is useful for monotonic relationships or ranked data. MAXScanner keeps the paired rows visible, rejects mismatched list lengths and shows the cross-deviation sum behind the coefficient rather than returning an unexplained number.
How to use this calculator
Paste X values and Y values in matching order; both lists must contain the same number of observations.
Choose Pearson for linear association in the raw measurements or Spearman for rank/monotonic association.
Review the coefficient, R², covariance and row table together; inspect the original data before treating a strong coefficient as a meaningful relationship.
Where people use it
- •Checking association between two measured variables
- •Comparing Pearson and rank-based correlation when outliers or nonlinear monotonic patterns matter
- •Auditing paired spreadsheet data before regression
Example: study hours and scores
For paired observations where scores generally rise with study hours, Pearson r approaches +1 when the relationship is close to a straight line. Spearman can remain high when the increase is monotonic but curved.
What the result does not assume
- •Correlation does not prove causation and can be driven by confounding variables, restricted ranges or outliers.
- •Pearson measures linear association. A near-zero Pearson r does not rule out a strong curved relationship.
- •Spearman uses average ranks for ties; different missing-value or tie policies in other software can change results if the datasets are not prepared the same way.
Frequently asked questions
What does a correlation of +1 or −1 mean?+
+1 is a perfect positive linear/rank relationship and −1 a perfect negative one for the selected method. Values near zero indicate little linear/rank association, not necessarily no relationship.
Pearson or Spearman?+
Use Pearson when a linear relationship in the original numeric scale is the target. Use Spearman when ranks or a monotonic relationship are more appropriate.
Is R² the same as correlation?+
For simple Pearson linear regression with an intercept, R² equals r². Squaring removes the sign, so it does not show direction.
Semantic next steps
Continue the calculation
These links move to a different input, formula or project stage rather than a keyword variation of this page.
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