This calculator measures the strength and direction of a linear relationship between two numeric variables for data analysis and quick statistical checks.
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Enter paired x and y values in matching order, with one pair for each observation. Remove pairs with missing values consistently, since shifting one column by a row produces impressive nonsense.
Pearson's coefficient is r = sum[(x - mean x) × (y - mean y)] / square root of {sum[(x - mean x)²] × sum[(y - mean y)²]}. The result ranges from -1 to 1.
For x values 1, 2, 3, 4 and y values 2, 3, 5, 6, Pearson's r is about 0.99. That indicates a very strong positive linear relationship in this small sample.
No. A strong correlation can result from a third variable, reverse causation, coincidence, or a genuinely direct relationship.
It means there is little linear association. A curved or otherwise nonlinear relationship may still exist, so a scatterplot is worth checking.
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