Causality refers to a cause-and-effect relationship where one event directly influences another, while correlation is a statistical relationship where two variables change together but may not have a direct cause-and-effect connection.
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Correlation refers to a relationship between two variables where they change together, while causality indicates that one variable directly causes a change in another. In simpler terms, correlation shows a connection, while causality shows a cause-and-effect relationship.
It is important to know the difference between correlation and causation because correlation only shows a relationship between two variables, while causation indicates that one variable directly causes a change in another. Understanding this distinction helps in making informed decisions and avoiding false assumptions based on misleading data.
Correlation is a relationship between two variables where they change together, but it does not imply causation. Cause and effect, on the other hand, indicates that one variable directly influences the other.
Correlation is a relationship between two variables where they change together, but it doesn't mean one causes the other. Causation, on the other hand, implies that one variable directly causes a change in the other.
Correlation is a relationship between two variables where they change together, while causation is when one variable directly causes a change in another variable. Just because two things are correlated does not mean that one causes the other.