Statistics

Correlation vs Causation in Data

By SC Editorial 2026-05-22 8 min read

Correlation measures whether two variables move together. Causation means one variable directly produces a change in another. Confusing them leads to flawed conclusions.

Pearson Correlation

r ranges from -1 to +1. r = 0.9 indicates strong positive association. Calculate with our Correlation Calculator.

Establishing Causation

Requires controlled experiments, temporal precedence, and ruling out confounding variables. Ice cream sales correlate with drowning deaths - both rise in summer (confounding variable: weather).

Regression Analysis

Regression predicts one variable from another but still does not prove causation. See the Regression Calculator.

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