Nonparametric calculator

Friedman test calculator

Perform non-parametric repeated measures ANOVA using the Friedman test for ranked metrics across 3+ matched conditions.

Run this test live in StatLab npm i @statlab/core

When to use it

Use when comparing 3+ repeated or matched conditions with ordinal or non-normal data.

Required Inputs

  • Matched subject rows
  • Repeated condition columns
  • Post-hoc correction choice

Mathematical Formula

Q_F = [ 12 / (n k (k+1)) ] * Σ R_j² - 3 n (k+1)

Reporting Cautions

  • Requires complete matched blocks without missing entries.
  • Follow up significant results with Nemenyi or Wilcoxon signed-rank post-hoc tests.

Code Snippets (Python, R, TypeScript)

Python (SciPy / Statsmodels) 
from scipy import stats
res = stats.friedmanchisquare(c1, c2, c3)
print(f"Q={res.statistic:.4f}, p={res.pvalue:.4f}")
R Language 
friedman.test(as.matrix(df))
TypeScript (@statlab/core) 
import { friedmanTest } from '@statlab/core';
const res = friedmanTest(matrix);

Developer Use Cases & Production Integrations

  • Comparing ranked performance metrics across 3+ database indexing strategies on matched queries.
  • Evaluating subjective LLM output ranks across model iterations.

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