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.
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Cause and effect in research studies refer to a direct relationship where one variable causes a change in another variable. Correlation, on the other hand, indicates a relationship between two variables but does not imply causation. In simpler terms, cause and effect shows a clear cause-and-effect relationship, while correlation shows a connection between variables without proving one causes the other.
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.
Cause refers to a direct relationship where one event leads to another, while correlation is a statistical relationship where two events occur together but may not have a direct cause-and-effect connection.
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.
Causation refers to a direct cause-and-effect relationship between two variables, where one variable directly influences the other. Correlation, on the other hand, refers to a relationship between two variables where they tend to change together, but one variable may not necessarily cause the change in the other.