Correlation vs Causation Statistics Example 1
Follow the full solution, then compare it with the other examples linked below.
Example 1
easyA study finds that towns with more ice-cream shops tend to have higher crime rates. Does this mean ice-cream shops cause crime? Explain.
Solution
- 1 Step 1: Identify the correlation: more ice-cream shops is associated with higher crime rates.
- 2 Step 2: Consider a lurking variable: larger towns have both more ice-cream shops and more crime simply because they have more people. Population size is a confounding variable.
- 3 Step 3: Correlation does not imply causation — the relationship between ice-cream shops and crime is explained by a third variable (population), not by a direct cause-and-effect link.
Answer
No, ice-cream shops do not cause crime. Both variables are related to a third factor — population size — which is the actual explanatory variable.
Correlation vs causation is a fundamental concept in statistics. Two variables may be correlated because they are both affected by a confounding variable, not because one causes the other. Establishing causation requires controlled experiments or rigorous study designs.
About Correlation vs Causation
Correlation shows that two variables move together in some pattern; causation means one variable actually makes the other change. Observing a correlation does not prove causation because a hidden third variable (confounder) may be driving both.
Learn more about Correlation vs Causation →More Correlation vs Causation Examples
Example 2 medium
A newspaper headline reads: 'Students who sleep more get higher grades — sleeping longer causes bett
Example 3 mediumData shows that countries with higher chocolate consumption per capita have more Nobel Prize winners
Example 4 hardA pharmaceutical company observes that patients who take their new supplement have lower rates of he