Correlation comparison

Paste comma-separated CSV with a header and 2 to 2000 complete rows. Use dot decimals with at most six decimal places and values from -1000000000 to 1000000000. No missing values are silently dropped. Extra columns are used only to preserve the original input in reports. Calculations use the required columns only. Processing stays on your device. Results use floating-point arithmetic. Charts show the supplied sample, not proof about a population. Choose confidence from 80 to 99 percent and a nonempty seed of at most 100 characters. Use x and y columns for matched pairs. Pearson measures linear association; Spearman uses average ranks for ties. Pearson uncertainty uses an approximate Fisher z interval, requiring at least four independent pairs and a bivariate-normal approximation; perfect correlations have no reported Fisher interval. Spearman uncertainty uses 500 seeded paired bootstrap resamples and requires at least 400 nonconstant resamples. Perfect rank correlations have no reported bootstrap interval. Small-sample and simulation uncertainty remain. Correlation is not causation or agreement. Search and sort change this comparison only. Copy result copies the summary. Download JSON or CSV for all observations, results, settings and method assumptions. Download SVG for the chart. One disposable worker per calculation, with a 10-second timeout. CSV supports up to 100 columns and 100000 cells through the shared parser. Paste comma-separated CSV with a header and 2 to 2000 complete rows. Use dot decimals with at most six decimal places and values from -1000000000 to 1000000000. No missing values are silently dropped. Extra columns are used only to preserve the original input in reports. Calculations use the required columns only. Processing stays on your device. Results use floating-point arithmetic. Charts show the supplied sample, not proof about a population. Choose confidence from 80 to 99 percent and a nonempty seed of at most 100 characters. Use x and y columns for matched pairs. Pearson measures linear association; Spearman uses average ranks for ties. Pearson uncertainty uses an approximate Fisher z interval, requiring at least four independent pairs and a bivariate-normal approximation; perfect correlations have no reported Fisher interval. Spearman uncertainty uses 500 seeded paired bootstrap resamples and requires at least 400 nonconstant resamples. Perfect rank correlations have no reported bootstrap interval. Small-sample and simulation uncertainty remain. Correlation is not causation or agreement. Up to 1,000,000 characters. Review the settings before running.