Correlation Coefficient Calculator

Work out Pearson’s correlation coefficient r between two variables and the coefficient of determination, and how strong and which way the link is.

Your details

Separate the values with commas or spaces

Separate the values with commas or spaces

Your data stays in your browser

Result

Enter both variables in the same order, then press “Calculate”.

Strength of the correlation

Your result will be marked here once calculated.

  1. NoneUnder 0.1
  2. Weak0.1–0.29
  3. Moderate0.3–0.49
  4. Strong0.5–0.69
  5. Very strong0.7 or more

The size of r gives the strength; its sign gives the direction.

Analysis and suggestions

Once calculated, this shows what your result means and suggestions based on your numbers.

Behind the result

Work out Pearson’s correlation coefficient r between two variables and the coefficient of determination, and how strong and which way the link is.

Example · r = Σ(x − x̄)(y − ȳ) ÷ √(Σ(x − x̄)² × Σ(y − ȳ)²)

r = 0.988, r² = 97.62%

How it is calculated

Comprehensive Calculator Guide

This calculator gives Pearson’s correlation coefficient r and r² between two variables, with the strength and direction of the linear link. Study hours and marks for six students give r = 0.99; temperature and hot coffee sales give r = −0.997.

Reading r

r runs from −1 to 1; the sign is the direction, the size the strength. r² is the share of variation explained. Correlation isn’t causation, and r misses curved links and is swayed by outliers.

How to Use

  1. Enter the first variable.
  2. Enter the second in the same order.
  3. Press “Calculate” to see r, r² and the strength.

Formula Used

r = Σ(x − x̄)(y − ȳ) ÷ √(Σ(x − x̄)² Σ(y − ȳ)²)

Practical Examples

Example 1
Study and marks: 0.988.
Example 2
Heat and hot coffee: −0.997.

Important Tips

  • Keep pairs aligned.
  • Plot first.
  • Use 10+ pairs.

Common Mistakes to Avoid

  • Inferring causation.
  • Misaligned lists.
  • Reading r = 0 as no relation.

Frequently Asked Questions

Strong r?
About 0.7+.
r vs r²?
Direction and strength vs share explained.
Spearman instead?
For ranks or non-linear links.

Read Also

Results are estimates for educational purposes and may vary depending on your situation and data sources.