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SigmaCalc
Detects monotonic relationships that Pearson's correlation can miss when the relationship isn't perfectly linear.
Spearman's correlation first converts each variable to ranks, then runs a standard Pearson correlation on those ranks — this makes it far less sensitive to outliers and doesn't require the relationship to be linear, only consistently increasing or decreasing.
Use Spearman when your data has outliers, is ordinal rather than truly continuous, or you suspect a monotonic-but-curved relationship (like diminishing returns) that a straight-line Pearson correlation would understate.
Spearman's rho (ρ)
0.8
Ranges from −1 (perfect negative) to +1 (perfect positive monotonic relationship)
What you entered
Rank the x values
1, 2, 3, 4, 5= 1, 2, 3, 4, 5Rank the y values
2, 1, 4, 3, 5= 2, 1, 4, 3, 5Pearson correlation of the ranks
r(rank x, rank y)= 0.8Result
ρ: 0.8
ρ = 0.8 — a strong positive monotonic relationship, based on ranks rather than raw values.