Which of the following best describes correlation?

Correlation refers specifically to the statistical relationship or association between two variables. It indicates how changes in one variable are related to changes in another variable. This relationship can be positive, negative, or nonexistent. For example, a positive correlation means that as one variable increases, the other tends to increase as well, whereas in a negative correlation, as one variable increases, the other tends to decrease.

Understanding correlation is crucial in data analysis because it helps to identify patterns and trends, which can be useful for making predictions. Correlation does not imply causation; just because two variables are correlated doesn't mean that one causes the other to change.

The other options do not accurately define correlation, as one pertains to average calculations, another focuses on probabilities, and the last suggests a relationship of cause and effect, which is distinct from what correlation measures.