🔍 Misleading correlations: a key lesson in data analysis#
📊 Did you know two variables can show a perfect correlation… without having anything to do with each other?
That’s what this site demonstrates with examples as absurd as they are entertaining: from searches for “zombies” correlating with college degrees, to margarine consumption “related” to divorce rates.
More information at the link 👇
🧠 For beginners:
A spurious correlation occurs when two things appear connected only because they follow a similar trend over time, but there is no real causal relationship.
In other words: just because two lines rise together doesn’t mean one causes the other.
⚠️ Why it matters in the real world:
- Prevents wrong conclusions in data projects
- Helps make evidence-based decisions
- Teaches skepticism toward “pretty” but misleading charts
- Reinforces the importance of critical thinking in analytics
💡 In short: correlation is not causation. And this site demonstrates that in a brilliant and entertaining way.
More information at the link 👇
