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Correlation coefficient calculator

Compute Pearson's correlation coefficient between two lists of numbers.

The Correlation coefficient calculator turns X values (comma-separated), Y values (comma-separated) into Correlation coefficient (r), instantly and for free. For instance, with X values (comma-separated) = 1, 2, 3, 4, 5 and Y values (comma-separated) = 2, 4, 5, 4, 6 it returns Correlation coefficient (r) = 0.853.

How to use it

  1. Enter your values: X values (comma-separated), Y values (comma-separated).
  2. Read the result instantly: Correlation coefficient (r).

Frequently asked questions

What does the Correlation coefficient calculator actually compute?

It takes X values (comma-separated) and Y values (comma-separated) and derives Correlation coefficient (r) from them. The calculation is live as you type, so the result updates on every change.

What information do I need to provide?

2 values: X values (comma-separated) and Y values (comma-separated). Nothing else is required — no account, no file upload.

Can you show a worked example?

With X values (comma-separated) = 1, 2, 3, 4, 5 and Y values (comma-separated) = 2, 4, 5, 4, 6, the calculator returns Correlation coefficient (r) = 0.853. Those figures come from running this exact tool, so you can reproduce them by entering the same values.

What happens if I enter larger values?

It moves a lot. Using X values (comma-separated) = 1, 2, 3, 5, 6 and Y values (comma-separated) = 2, 4, 6, 5, 7 instead, Correlation coefficient (r) goes from 0.853 to 0.84 — which is why it is worth testing a few scenarios rather than trusting a single figure.

What does it give for smaller values?

Scaled down to X values (comma-separated) = 1, 2, 3 and Y values (comma-separated) = 2, 4, 5, Correlation coefficient (r) comes out at 0.982. The relationship is worth checking at both ends before you rely on a single result.

When would I actually use this?

Summarising a dataset before drawing conclusions from it, checking whether a difference between two groups is real, and putting an interval around an estimate.

What is the most common mistake?

Reading a p-value as the probability that the hypothesis is wrong. It is the probability of seeing data at least this extreme if the null were true — a different statement, and a much weaker one.

What is the difference between the Correlation coefficient calculator and the Coefficient of variation calculator?

This one returns Correlation coefficient (r); the Coefficient of variation calculator returns Coefficient of variation and Mean. That is the whole difference — open the one whose figure you need.

Is there a tool for the next step?

Gini coefficient calculator is the closest one after this: The Gini coefficient of a distribution — the standard measure of inequality, from 0 (everyone equal) to 1 (one person has everything). Paste any set of non-negative values — incomes, wealth, market shares — and it computes the Gini and expresses it as a percentage, the way income inequality is usually reported.

What else is worth having open alongside it?

Spearman Rank Correlation Calculator and Expected value calculator — they come up in the same task often enough to be worth a second tab.

Further reading

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