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Correlation Coefficient Calculator

Pearson's correlation coefficient between two sets of paired values — how strongly they move together, and whether the relationship is statistically significant.

Pearson's r measures how closely two variables move together on a straight line, from −1 (perfectly opposed) through 0 (no linear relationship) to +1 (perfectly together).

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Results
Correlation (r)
0.95119
r² — variance explained
Pairs
Strength
Two-tailed p-value
What it does not say
Reviewed September 2026. Pure mathematics: the result does not depend on where you are. Terminology follows the Australian Curriculum (maths, brackets, decimal point).
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About correlation coefficient

How the correlation coefficient calculator works

Pearson's r measures how closely two variables move together on a straight line, from −1 (perfectly opposed) through 0 (no linear relationship) to +1 (perfectly together). It is the covariance divided by the product of the two standard deviations, which strips out the units so r is comparable across any pair of measurements.

Two cautions come with it. r² is the share of variance explained, and it is always smaller than r — a correlation of 0.7 explains only 49% of the variation. And r measures *linear* association only: a perfect parabola has an r near zero, and correlation never establishes cause.

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

Worked examples

InputsCorrelation (r)Note
A strong positive pair0.95119r ≈ 0.91
A perfect straight line1r = 1
Perfectly opposed-1r = −1

Frequently asked questions

What does the correlation coefficient measure?

How closely two variables move together on a straight line, from −1 through 0 to +1.

What is a strong correlation?

Above about 0.7 in absolute value is usually called strong, 0.5 moderate and below 0.3 weak — though what counts as strong varies a great deal by field.

What is r²?

The share of variance in one variable explained by the other. It is always smaller than r: a correlation of 0.7 explains only 49%.

Does correlation prove causation?

No. It measures association. A third variable, coincidence or reverse causation can all produce a high r.

Can r miss a real relationship?

Yes — it only sees straight lines. A perfect parabola gives an r of zero despite a perfect relationship.

Where these figures come from

Last checked: September 2026. Formulas are fixed by mathematics and do not change with tax years or regulations.