Paste paired values for two variables and get Pearson's r or Spearman's rho with an exact p value, confidence interval, and APA 7 write-up. Values are matched by position.
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Get QuantaPearson's r measures the strength of a linear relationship between two continuous variables and is the default when both variables are roughly normally distributed without extreme outliers.
Spearman's rho ranks the data first, so it measures monotonic association. Choose it for ordinal variables (like Likert items), skewed distributions, or data with outliers.
Correlations run from -1 to +1. By common benchmarks, |r| around .10 is small, .30 medium, and .50 large. The p value tests whether the correlation differs from zero; with large samples, even tiny correlations become significant, so always interpret the size of r, not just the p value. r² tells you the proportion of variance the two variables share.
The confidence interval uses the Fisher z transformation. For Spearman, the interval is approximate.
A significant correlation says the variables move together. It cannot say which causes which, or whether a third variable drives both. Design, not statistics, answers causal questions.