← L² Lab
🧠 Critical Thinking
Card 26
📈 ≠ ➡️

Just because two things rise together, does one cause the other?

💭 How to Think About This

Ice cream sales rise - drownings rise! Does ice cream cause drowning? NO! Summer causes BOTH! This is the #1 statistical error: confusing CORRELATION (things happening together) with CAUSATION (one causing the other). Let's dive deeper!

🔒 Start writing to unlock hints

CORRELATION = two things happening together or following patterns. CAUSATION = one CAUSES the other. Correlation is easy to find - causation requires proof! Just because A and B move together doesn't mean A→B, could be B→A, C→both, or coincidence!

CONFOUNDING VARIABLE = hidden third factor causing both! Ice cream/drowning example: SUMMER is confounding variable (causes both). Shoe size correlates with reading ability - does big feet = smart? NO! AGE is confounding (older = bigger feet AND better reading)!

Maybe B causes A, not A causes B! "Sick people take more medicine" - does medicine cause sickness? NO! REVERSE: sickness causes medicine-taking! "Firefighters are present at fires" - do firefighters CAUSE fires? Always consider direction!

To prove A causes B need: (1) A happens before B, (2) Correlation exists, (3) NO other explanation (ruled out confounders), (4) Mechanism (HOW does A cause B?). That's why controlled experiments matter - isolate the one variable!

Correlation ≠ Causation! Things can move together without one causing the other!

The four possibilities when A and B correlate:

1. A causes B: Smoking → lung cancer ✓

2. B causes A: (reverse causation) Wealth → education? Or education → wealth?

3. C causes both: (confounding) Summer → ice cream AND drowning

4. Coincidence: Nicolas Cage movies correlate with swimming pool drownings (meaningless!)

Famous spurious correlations:

• Divorce rate in Maine correlates with margarine consumption

• Number of people who drowned falling into pool correlates with Nicolas Cage films

• Shoe size correlates with salary (age is confounder!)

Requirements for causation:

✓ Temporal precedence (cause before effect)

✓ Correlation exists

✓ No plausible alternative explanations

✓ Dose-response (more A = more B)

✓ Plausible mechanism (HOW?)

✓ Consistency across studies

Critical question: When seeing correlation, always ask: "What else could explain this pattern?"

🤔 Which thinking lens(es) did you use?

Select all the lenses you used: