AP CSP Day 13: Correlation vs. Causation
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Correlation describes a statistical relationship between two variables that tend to change together, while causation means one variable directly causes changes in the other. Observational data can establish correlation but cannot prove causation without controlled experimentation. The AP CSP exam frequently presents scenarios where data shows a correlation and asks whether a causal conclusion is justified. A classic exam pitfall is accepting a causal claim based solely on a strong correlation in a dataset.
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Correlation vs. Causation
What Is Correlation?
Two variables are correlated when they tend to change together. As one increases, the other consistently increases (positive correlation) or decreases (negative correlation). Correlation is measured from data observations.
Why Correlation Is Not Causation
Observational data shows what happens together, not what causes what. A third variable (confounder) often explains why two unrelated variables appear correlated. Only a controlled experiment, where all other variables are held constant, can establish causation.
Practice Question
A study finds that cities with more ice cream shops tend to have higher rates of sunburn. Which of the following is the best explanation?
This is a classic confounding variable example. Warm, sunny weather independently causes both higher ice cream sales and more sunburn. The two variables are correlated but neither causes the other — a third factor (weather) drives both.
A) There is no plausible mechanism by which ice cream causes skin damage from UV radiation. B) While sunburned people might buy ice cream, this reverses the observed correlation and still ignores the confounding variable. D) The data pattern is real and consistent — the issue is interpretation, not measurement error.
Students assume that because two variables increase together, one must cause the other. Correlation between two variables often results from a shared underlying cause.
When you see two correlated variables, always ask: Could a third variable explain both? This is the most common correct answer on AP CSP correlation vs. causation questions.
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