Understanding Correlation vs. Causation

Sep 19, 2024

Lecture on Correlation vs. Causation

Introduction

  • Speaker: Peter van de Ven
  • Topic: Dangers of misinterpreting correlations as causations.

Example 1: Ice Cream and Drownings

  • Plotting a graph of ice cream sales vs. drownings shows an upward trend.
  • Incorrect conclusion: Ice cream causes drownings.
  • Actual cause: Nice weather causes both increased swimming and ice cream sales.
  • Lesson: Correlation does not imply causation.

Logical Mistake

  • Jumping to incorrect conclusions about causality when seeing a correlation is a common logical error.

Example 2: Marriage and Men's Longevity

  • Statistics show married men live longer than single men.
  • Misinterpretation: Marriage causes longer life for men.
  • True causation: Healthy, wealthy, and well-educated men (who have higher life expectancy) are more likely to marry.
  • Takeaway: High life expectancy leads to higher marriage rates, not the other way around.

Example 3: Children Sleeping with Lights On

  • 1999 study linked night lights to myopia in children.
  • Initial advice: Turn off lights to prevent short-sightedness.
  • Correction: Short-sightedness is genetic; short-sighted parents are likely to leave lights on and have short-sighted children.
  • Lesson: Simple correlation mistake; causation was misunderstood.

Example 4: Self-Esteem and Academic Success

  • 1970s research linked high self-esteem with good grades.
  • Misconception: High self-esteem leads to good grades.
  • Actual direction: Good grades boost self-esteem.
  • Problem: Children with high self-confidence but no achievements end up with low self-esteem.

Broader Implications

  • Incorrect correlations have been drawn in various contexts (e.g., vaccines and autism, female bankers and financial crises).
  • Strong correlation is insufficient to prove causation.
  • Requirement for causation: Understand the why and how of the relationship.

Conclusion

  • Always question causal claims based on correlation.
  • When in doubt, remember the ice cream analogy.

Note: These notes summarize key points from a lecture on understanding the difference between correlation and causation, using various illustrative examples.