Correlation Calculator (Pearson & Spearman)
Measure the strength and direction of the relationship between two numeric variables. Paste two columns straight from Excel, Google Sheets or SPSS and get Pearson's r with its significance test and Fisher 95% confidence interval — and Spearman's rank correlation ρ on the same screen, so you can see immediately whether outliers or non-linearity change the conclusion. A Shapiro-Wilk normality check runs automatically and suggests when the rank-based Spearman coefficient is the safer choice. This is a statistical correlation tool (not a stock-portfolio calculator); results match R's cor.test() to at least six significant digits.
AI Report
Let AI interpret your results: a downloadable Word document in APA 7 / business report format.
Frequently asked questions
How do I report a correlation in APA 7 format?
Report r with degrees of freedom (N − 2), the p-value and ideally the confidence interval, e.g.: "Study time and exam score were strongly positively correlated, r(10) = .99, p < .001, 95% CI [.96, 1.00]." The AI Report writes the complete APA sentence and interpretation for you.
Should I use Pearson or Spearman correlation?
Pearson r measures linear association and assumes roughly normal variables without extreme outliers. Spearman ρ works on ranks, so it is robust to outliers and captures any monotonic relationship. If the two disagree noticeably, inspect a scatterplot — this tool shows both by default.
What counts as a strong correlation?
Common benchmarks (Cohen): |r| ≈ .10 small, .30 medium, .50+ large. Context matters — in psychology .40 may be impressive, in physics it may be weak. Statistical significance only says the correlation is unlikely to be zero, not that it is large.
Does correlation imply causation?
No. A significant correlation means the variables move together; it cannot tell you which causes which, or whether a third variable drives both. Causal claims need experimental or careful quasi-experimental designs.