Upload a CSV, map your before and after columns measured on the same subjects, and get the paired t-test with a confidence interval, a Wilcoxon signed-rank cross-check, the effect size, and the share of pairs that improved. Free.
Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size — sign up to analyze your full dataset.
Comparing before and after...
Sent to — before-vs-after scatter, distribution of changes, the paired t-test with confidence interval, Wilcoxon signed-rank cross-check, effect size, R code, and AI insights.
Analyze another fileThe analysis works on the within-pair change (after minus before) for every subject. It runs a paired t-test for the mean change with a 95% confidence interval, a Wilcoxon signed-rank test as a distribution-free cross-check, and Cohen's dz for the standardized effect size. A Shapiro-Wilk check on the differences decides whether the parametric t-test or the rank-based Wilcoxon result is the safer headline, and the report also shows the share of pairs that increased, decreased, or stayed the same.
Use it whenever the same unit is measured twice — before and after a change, treatment and control on the same subject, or two raters scoring the same items — and you want to know if the change is real and how big it is.
Not for comparing two independent groups of different subjects (use the group comparison tool), and not for two categorical columns (use a categorical association tool).
Built for: Analysts, researchers, and operators measuring the same subjects twice
Typical data source: Any spreadsheet or CSV with a before column and an after column measured on the same subjects, one pair per row
Two numeric measurements on the same subjects, one pair per row. For example, a test score before and after training:
Minimum 6 rows · Best with 20-10,000 paired rows
Standard-library analysis: did a paired or repeated measurement actually change? Map a before column and an after column measured on the same subject — before vs after, treatment vs control on the same unit, two raters on the same items — and get the paired t-test with a confidence interval on the mean change, a Wilcoxon signed-rank cross-check, Cohen's dz effect size, a normality check that picks the safer headline, and the share of pairs that moved up or down.
Every pair plotted before against after with a no-change diagonal — points above the line went up, points below went down.
How much each pair changed, as a histogram — where it centers relative to zero shows the typical movement.
The paired t-test with its confidence interval, the Wilcoxon signed-rank cross-check, the effect size, and the normality check that picks the headline.
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Did the before-and-after actually change?
Map your before column and your after column measured on the same subjects. You get the paired t-test with a confidence interval on the mean change, a rank-based cross-check, the effect size, and the share of pairs that improved — in one report.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.
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