als-statistics/tests/golden/edge-ttest.test.js

Modular JS statistics toolkit for Node.js and the browser: descriptive stats, correlations (Pearson/Spearman/Kendall), t-tests & ANOVA (Student/Welch), reliability (Cronbach’s alpha), regression (linear/logistic), clustering (DBSCAN/HDBSCAN), and table/co

import test from 'node:test';
import assert from 'node:assert/strict';
import { IndependentTTest } from '../../lib/analyze/compare-means/independent-t-test.js';
import { PairedTTest } from '../../lib/analyze/compare-means/paired.js';
import { OneSampleTTest } from '../../lib/analyze/compare-means/one-sample.js';

test('Paired trims to min length and computes diffs A-B', () => {
  const a = [1, 2, 3, 4, 5];
  const b = [1, 1, 2, 3]; // shorter
  const t = new PairedTTest({ A: a, B: b });
  assert(t.n >= 2);
  // meanDelta should be > 0 because A-B mostly positive
  assert.ok(typeof t.meanDelta === 'number');
});

test('Independent: Student == Welch on equal variances (approx)', () => {
  const g1 = [1, 2, 3, 4, 5, 6];
  const g2 = [2, 3, 4, 5, 6, 7];
  const stud = new IndependentTTest({ g1, g2 }, false);
  const wel = new IndependentTTest({ g1, g2 }, true);
  // df differ in general, но t близки
  assert.ok(Math.abs(stud.t - wel.t) < 1e-6);
});

test('One-sample: shifting mu0 flips t sign', () => {
  const x = [2, 3, 4, 5, 6];
  const t1 = new OneSampleTTest({ X: x }, 0);
  const t2 = new OneSampleTTest({ X: x }, 10);
  assert.ok(t1.t > 0 && t2.t < 0);
});