What does correlation in statistics indicate?

Correlation in statistics indicates the degree to which two variables move in relation to each other. This relationship can be positive, negative, or nonexistent. A positive correlation means that as one variable increases, the other tends to increase as well, while a negative correlation indicates that as one variable increases, the other tends to decrease. Correlation is measured by a correlation coefficient, which quantifies the strength and direction of the relationship between the variables. It is important to understand that correlation does not imply causation; it simply describes how two variables relate in terms of their movements.

The other options do not accurately capture the essence of correlation. For instance, the notion of two variables moving independently is counter to the concept of correlation, which is fundamentally about their interrelationship. A perfect linear relationship would represent an extreme case of correlation, but correlation encompasses a broader range of relationships, not limited to perfect scenarios. Lastly, averaging two variables does not reflect their correlation; rather, it would give a singular measure without indicating how they relate to one another.