Correlation vs Causation
Association does not prove one thing causes another.
Key idea
Association does not prove one thing causes another.
In depth
Two variables may be associated because X causes Y, Y causes X, a third (confounding) variable causes both, or by chance. Only well-designed randomised experiments can establish causation.
Worked example
Ice cream sales and drownings both rise in summer; heat is the confounder.
Real-world uses
- Questioning headlines that link ice cream sales to drowning or screen time to grades
Common mistake
Stating that a correlation shows one thing causes the other.
How to learn this
- Read the key idea and say it in your own words.
- Work through the worked example, then try a similar problem.
- Use the interactive lesson’s visual and mini-quiz to check the pattern.
Frequently asked questions
What is Correlation vs Causation?
Association does not prove one thing causes another. It is a topic at the advanced level in Probability & Statistics.
Where is Correlation vs Causation used in real life?
Real-world examples: Questioning headlines that link ice cream sales to drowning or screen time to grades.
What should I learn before Correlation vs Causation?
Make sure you are comfortable with Residuals and R², the previous topic in Probability & Statistics.
What is a common mistake with Correlation vs Causation?
Stating that a correlation shows one thing causes the other.
How can I practise Correlation vs Causation?
Open the interactive lesson, play with the visual, then answer the three-question mini-quiz. Getting two right marks the topic complete.
What comes after Correlation vs Causation?
Move on to Simpson’s Paradox next.
Related advanced topics in Probability & Statistics
- Quartiles and IQR – Quartiles split data into four parts; IQR = Q3 − Q1.
- Box Plots – Five-number summary visualised.
- Outliers – Values beyond 1.5 IQR from the quartiles.
- Variance – Average squared deviation from the mean.
- Standard Deviation – Square root of variance; typical spread.
- Sample vs Population Variance – Divide by n−1 for sample variance.