Front

What is the difference between causation and association?

Back

Causation indicates that one event is the result of the occurrence of another event, while association indicates a relationship or correlation between two events without implying that one causes the other.

Front

Define causation.

Back

Causation is the action of causing something; it refers to a relationship where one event (the cause) directly affects another event (the effect).

Front

Define association.

Back

Association refers to a relationship or correlation between two variables or events, where changes in one may relate to changes in the other, but do not imply a direct cause-and-effect relationship.

Front

Example of causation: More hours worked leads to more money earned. What does this illustrate?

Back

This illustrates a direct cause-and-effect relationship where working more hours directly results in earning more money.

Front

Example of association: Never washing your game socks and your team on a winning streak. What does this illustrate?

Back

This illustrates a correlation where the two events occur together, but one does not cause the other.

Front

What is a common misconception about association?

Back

A common misconception is that if two events are associated, one must cause the other, which is not necessarily true.

Front

What is an example of a situation that shows causation?

Back

If a student studies more hours, they improve their grades. This shows causation because studying directly affects grades.

Front

What is an example of a situation that shows association?

Back

The number of ice cream sales and the number of people at the beach. Both increase in summer, but one does not cause the other.

Front

How can you determine if a relationship is causal?

Back

To determine if a relationship is causal, look for evidence of a direct effect, conduct experiments, or analyze data to rule out other factors.

Front

What is a confounding variable?

Back

A confounding variable is an outside influence that changes the effect of a dependent and independent variable, potentially leading to false conclusions about causation.