Correlation vs. Causation

Front

What is the difference between correlation and causation?

Back

Correlation indicates a relationship between two variables, while causation implies that one variable directly affects the other.

Tags

CCSS.RI.7.7

CCSS.RI.8.7

CCSS.RI.9-10.7

CCSS.RL.7.7

CCSS.RL.8.7

Front

Provide an example of correlation that does not imply causation.

Back

Ice cream sales increase as temperature increases.

Tags

CCSS.HSS.ID.C.9

Front

What does a correlation coefficient of 0 indicate?

Back

A correlation coefficient of 0 indicates no relationship between the two variables.

Tags

CCSS.HSS.ID.B.5

Front

What is a positive correlation?

Back

A positive correlation occurs when two variables move in the same direction; as one increases, the other also increases.

Tags

CCSS.HSS.ID.B.5

Front

What is a negative correlation?

Back

A negative correlation occurs when two variables move in opposite directions; as one increases, the other decreases.

Tags

CCSS.HSS.ID.B.5

Front

What is an example of a situation where correlation does not imply causation?

Back

The number of people at the beach increases with temperature, but temperature does not cause people to go to the beach.

Tags

CCSS.HSS.ID.C.9

Front

What is a spurious correlation?

Back

A spurious correlation is a relationship between two variables that is caused by a third variable, rather than a direct relationship between the two.

Tags

CCSS.HSS.ID.C.9

Front

What is the significance of understanding correlation in data analysis?

Back

Understanding correlation helps identify relationships between variables, but it is crucial to avoid assuming causation without further evidence.

Tags

CCSS.HSS.ID.C.9

Front

What is an example of a correlation that could be misinterpreted as causation?

Back

Hours spent in the mall and amount of money spent could be misinterpreted as one causing the other.

Tags

CCSS.HSS.ID.C.9

Front

What is the role of controlled experiments in establishing causation?

Back

Controlled experiments help establish causation by isolating variables and determining if changes in one variable directly affect another.