A relationship refers to a connection or association between two or more variables. In statistics, it typically involves examining how changes in one variable are related to changes in another variable.
Think of a relationship like a seesaw - when one side goes up, the other side goes down. Similarly, in statistics, a relationship between variables can be positive (both variables increase together), negative (one variable increases while the other decreases), or even non-existent.
Correlation: Correlation measures the strength and direction of the relationship between two quantitative variables.
Causation: Causation refers to a cause-and-effect relationship where changes in one variable directly influence changes in another variable.
Association: Association describes the presence of a relationship between two variables but does not necessarily imply causation.
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