{
  "slug": "spearman-correlation",
  "name": "Spearman correlation",
  "aliases": [
    "Spearman rho",
    "Rank correlation"
  ],
  "definition": "How closely two metrics move together in rank order, over aligned time buckets.",
  "category": "Statistics",
  "type": "statistical verdict",
  "unit": "coefficient between −1 and 1",
  "direction": "neutral",
  "verification": "verified",
  "calculation": "Both aligned series are converted to ranks, with tied values sharing an average rank, and the product-moment coefficient is then computed on those ranks, it is literally the value-based routine applied to ranks. The probability is produced the same way too, which means it inherits the same normal approximation rather than an exact distribution.",
  "aggregation": "One coefficient per pair of series.",
  "grain": "One value per metric pair, date range and bucket size.",
  "dimensions": [
    "bucket"
  ],
  "requiredFilters": [
    "date_range"
  ],
  "sources": [
    "search-console",
    "web-analytics",
    "google-ads",
    "rank-tracking",
    "lighthouse"
  ],
  "reports": [],
  "skills": [
    "cross-domain-correlator",
    "anomaly-investigator"
  ],
  "verbs": [
    "correlate_domains"
  ],
  "rungs": [
    "R5",
    "R2"
  ],
  "levers": [],
  "questions": [
    "Do citations and sessions move together?",
    "Is the relationship robust to outliers?"
  ],
  "interpretation": "The robust reading of the same question. Because it works on ranks, a single extreme week cannot dominate it and a real but curved relationship still shows. When the two coefficients disagree sharply, that disagreement is itself the finding.",
  "caveats": [
    "Its significance carries the same approximation as the value-based coefficient: a normal approximation with a Cornish to Fisher correction, anti-conservative on short series and never stated on the card. It is also the standard coefficient's probability formula applied to ranks, which is a further approximation on top.",
    "Correlation is not causation; the same caveat and sample size ride on the payload.",
    "Ranking discards magnitude, so a relationship that is strong in rank order can be small in absolute terms.",
    "Ties share an average rank, which flattens the coefficient on series with many repeated values.",
    "Same minimum of three buckets per side and three aligned buckets as the value-based coefficient.",
    "An insignificant coefficient is reported as no detectable relationship at this power."
  ],
  "freshness": "varies by site, priority URLs can run nightly; most pages far less often. The collection date rides on the card rather than being assumed.",
  "failureModes": [
    "Reading rank agreement as proportional movement.",
    "Reporting whichever of the two coefficients is larger without saying which was used."
  ],
  "notSameAs": [
    {
      "slug": "pearson-correlation",
      "why": "Spearman works on ranks and Pearson on values. Where they disagree, the relationship is either non-linear or outlier-driven, and reporting only one hides that."
    }
  ],
  "related": [
    "pearson-correlation",
    "significance-p-value"
  ],
  "workflows": [],
  "lastVerified": "2026-08-04"
}