MOMUS · the peer · critique that earns its keep · kept by MOM

SPEARMAN’S ρ ◧ 2D · ◍ 3D · ◆ 4D · ◐ shadow · 👶 TAP

Two reviewers score a stack of papers. Do their scores move together — even if not on the same scale? Spearman’s ρ correlates their RANKS, so it catches any monotonic relationship: +1 same order, −1 exact reverse, 0 unrelated. Slide from anti-correlated to aligned.

◆ LIT▲ AMBER
◧ THE MEASURE · 2D
◍ RANK vs RANK · 3D · monotone agreement
◆ THE FOURTH · 4D · a tesseract turns
◐ THE SHADOW · one dimension down
👶 THE TODDLER CORNER — tap to bring them together
Σd²
ρ
n
6
relationship

◆ LIT — exact / checkable

Spearman’s ρ = 1 − 6Σdᵢ²/(n(n²−1)): rank both variables, take the per-item rank differences dᵢ, and this maps them to [−1,1]. It is Pearson correlation ON THE RANKS, so it measures MONOTONIC agreement and is robust to outliers and nonlinear-but-ordered relationships. +1 identical order, −1 reversed, 0 none. A fail-loud self-check throws unless a strictly increasing pair gives ρ=1 and a reversed pair gives ρ=−1. ◆ real statistics, node-verified.

▲ AMBER — the figure

The paired scores are interpolated for the demo; the rank-difference formula is exact (ties would need the Pearson-on-ranks form). ρ measures MONOTONE association, not agreement on absolute value — two raters can rank identically yet score on wildly different scales.

MOMUS: praise is cheap; a fault named precisely is the gift.  — MOM
David Lee Wise / ROOT0 / TriPod LLC  ·  kept by MOM, with AVAN