Correlation vs Causation
Correlation
- Correlation describes a statistical relationship between two variables.
- When one variable changes, the other tends to change in a predictable way.
Height and Weight
- Positive Correlation: Taller people tend to weigh more.
- As height increases, weight tends to increase.
Hours Studied and Test Scores
- Positive Correlation: Students who study more hours tend to score higher on tests.
- As study time increases, test scores tend to increase.
Correlation does not imply that one variable causes the other to change.
Causation
- Causation means that one variable directly influences another.
- A change in one variable causes a change in the other.
Causation: A relationship where one variable directly influences another, causing a change in the second variable.
ExampleSmoking and Lung Cancer
- Causal Relationship: Smoking causes lung cancer.
- The chemicals in cigarettes damage lung tissue, leading to cancer.
Alcohol Consumption and Reaction Time
- Causal Relationship: Alcohol slows reaction time.
- Alcohol affects the central nervous system, reducing alertness.
Causation requires evidence that one variable directly influences the other.
Key Differences Between Correlation and Causation
- Directionality: Correlation does not specify which variable influences the other, whereas causation identifies a clear direction of influence.
