Compare Two Correlations Calculator

Test whether two independent correlations differ significantly. Enter each correlation and the sample size it came from.

p-value (difference)
0.171
no significant difference
1.368
z
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How the test works

This test uses the Fisher r-to-z transformation to convert each correlation to a value that is approximately normally distributed, then compares the two using their sample sizes. It applies to two independent correlations, for example the same relationship measured in two separate groups of respondents.

Reading the result

A p-value below 0.05 means the two correlations differ by more than sampling noise would explain. A larger p-value means you cannot rule out that both groups share the same underlying correlation. Larger samples make the test more sensitive to real differences.

Frequently asked questions

Can I compare correlations from the same sample?

No. This calculator assumes the two correlations come from independent samples. Comparing overlapping correlations within one sample needs a different, dependent-samples test.

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