Correlation Coefficient Calculator
Pearson correlation measures the direction and strength of a linear relationship between paired numbers.
How to use this calculator
- Enter the values requested by the Correlation Coefficient and keep all units consistent.
- Check the formula and worked example before relying on the displayed result.
- Change one input at a time when comparing alternative scenarios.
Formula and method
r = Σ[(x − mean x)(y − mean y)] ÷ √(Σ(x − mean x)² Σ(y − mean y)²)
- The calculator applies the stated relationship to the inputs entered by the visitor. Intermediate calculations use full numeric precision before display rounding.
- Correlation does not establish that one variable causes the other.
Worked examples
Worked example: Correlation Coefficient
X values 1, 2, 3; Y values 2, 4, 6
The second series is exactly twice the first, so the correlation is +1.
The second series is exactly twice the first, so the correlation is +1.
Understanding the result
Use the output as a calculation for the chosen assumptions, not as an explanation of why a real-world result occurred.
Correlation does not establish that one variable causes the other.
Important notes
Correlation does not establish that one variable causes the other.
Confirm the units, source measurements, rounding convention and context before using the result for a real project or decision.
Frequently asked questions
What does this Correlation Coefficient calculate?
Pearson correlation measures the direction and strength of a linear relationship between paired numbers.
Which assumptions matter most?
Correlation does not establish that one variable causes the other.
Can the result replace professional or domain-specific guidance?
No. The tool provides arithmetic under its stated assumptions; check applicable specifications, accounting conventions, standards or qualified guidance for consequential decisions.
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This page provides a calculation tool plus explanatory information so you can understand what the result means and when the underlying method may not fit your situation.