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Correlation Calculator — Pearson & Spearman with Paired-Data Working

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No hidden assumptions. Inputs, units and the working stay visible so you can check the calculation.

Correlation method X values Paste a spreadsheet column or a comma/space/new-line separated list. Invalid tokens are rejected.Y values Paste a spreadsheet column or a comma/space/new-line separated list. Invalid tokens are rejected.Displayed precision

Calculated result

Pearson r = 1

Pairs n: 6

R²: 1

Raw-data Pearson r: 1

Sample covariance: 8.4

Raw-data best-fit slope y on x: 1

Paired data

#	X	Y	X used	Y used
1	2	1	2	1
2	4	3	4	3
3	5	4	5	4
4	7	6	7	6
5	8	7	8	7
6	10	9	10	9

Show the working

1. Use the original numeric X and Y values.
2. Compute means: x̄ = 6, ȳ = 5.
3. Cross-deviation sum Sxy = 42; Sxx = 42; Syy = 42.
4. Pearson r = Sxy ÷ √(Sxx×Syy) = 1.

Association is not causation. Inspect the paired data and the shape of the relationship; a single coefficient can hide outliers, clusters or curved patterns.

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