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Visual Guides/Correlation vs Causation
Data & Analysis

Correlation vs Causation: The Visual Guide

Ice cream sales and shark attacks are strongly correlated, but ice cream doesn't cause sharks. Explore confounding variables, generate spurious correlations, and learn when correlation hints at causation.

Confound revealed
Spurious pairs: 0/2
Causal diagram selected

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The Ice Cream Paradox

Both ice cream sales and shark attacks spike every year at the same time. Are they causally linked?

Pearson r

0.99

very strong positive

010203040500481216Ice Cream Sales ($1000s/month)Shark Attacks (count/month)

Correlation ≠ Causation

Correlation

Two variables move together, but neither necessarily causes the other.

Ice Cream Sales ↔ Shark Attacks

Bidirectional: no causal claim

↔Association only; direction unknown

Causation

One variable directly causes changes in another via a mechanism.

Temperature → Ice Cream Sales

Directional: mechanism exists

→A causes B through a real pathway

Key rule: Correlation does not imply causation. And causation does not even guarantee a visible correlation: opposing pathways or nonlinear effects can cancel the linear signal.

Common Cause (Confounder)

Z→X, Z→Y

A third variable Z causes both X and Y, creating a spurious correlation.

Reverse Causation

Y→X (not X→Y)

You assume X→Y but actually Y→X. Classic in economics and medicine.

Mediation

X→Z→Y

X causes Z which causes Y. The effect is indirect, but still causal.

Causal Diagrams

Which causal structure best explains the ice cream / shark correlation?

Click a causal diagram above to read its explanation.

Generate Spurious Correlations

Real data, zero causal meaning, and a generator to find your own "surprising" correlations.

Famous Real Spurious Correlations

Cheese Consumption vs Bedsheet Deaths

After Tyler Vigen, Spurious Correlations (data approximated)

Per-capita cheese (lbs/yr)r = 0.95

Bedsheet entanglement deaths

Nicolas Cage Films vs Pool Drownings

After Tyler Vigen, Spurious Correlations (data approximated)

Nicolas Cage films (per year)r = 0.75

Pool drowning deaths

Spelling Bee Word Length vs Spider Deaths

After Tyler Vigen, Spurious Correlations (data approximated)

Letters in winning wordr = 0.49

Spider-related deaths

Random Correlation Generator

Two completely unrelated random variables

Generated

0

With enough random pairs, you'll find high correlations by chance alone. This is called p-hacking or the multiple comparisons problem. The correlation is mathematically real; the causal meaning is not.

Real Correlations That Don't Imply Causation

Click each card to expand and see the hidden confounding variable.

Each card uses a small illustrative dataset that sketches the real-world pattern; the r shown is computed from the plotted points, not taken from a published study.

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