Difference Between Correlation and Causation
1. Correlation
- Definition: Correlation refers to a statistical relationship or association between two variables. When two variables are correlated, they change together, but this doesn’t necessarily mean one causes the other.
- Key Point: Correlation does not imply causation.
- Example:
- Scenario: Ice cream sales and drowning incidents are positively correlated.
- Interpretation: Both tend to increase during summer, but ice cream sales don’t cause drowning. The common factor (hot weather) influences both.
2. Causation
- Definition: Causation indicates that one event is the direct result of another. In this case, a cause-and-effect relationship exists between the two variables.
- Key Point: Establishing causation often requires controlled experiments or additional evidence.
- Example:
- Scenario: Smoking and lung cancer.
- Interpretation: Research shows that smoking causes lung cancer through prolonged exposure to harmful substances in cigarettes.
Data Analytics Training in Pune
Data Analytics Classes in Pune
