What statistical concept does not imply causation but rather indicates the extent of relationship between paired numbers?

The concept that does not imply causation but indicates the extent of the relationship between paired numbers is correlation. Correlation measures the strength and direction of the linear relationship between two variables. It quantifies how changes in one variable are associated with changes in another without asserting that one variable causes the change in the other. This distinction is critical in data analysis, as establishing correlation does not provide evidence of a causal relationship.

In contrast, regression analysis often explores the relationship between variables and attempts to establish predictive relationships, which can imply causation under certain conditions. Covariance is a measure that indicates the direction of the linear relationship between variables but does not standardize this value, making it less interpretable than correlation. Descriptive statistics summarize and describe the features of a dataset without exploring relationships between specific paired variables. Therefore, correlation is the most appropriate term for indicating the extent of a relationship between paired numbers without inferring causality.