A negative correlation coefficient indicates what relationship between two variables?

A negative correlation coefficient indicates an inverse relationship between two variables, meaning that as one variable increases, the other variable decreases. This can be interpreted as a predictable pattern: for instance, if we take height and weight as variables, one might find that, in certain contexts, as the amount of exercise increases (first variable), the amount of weight might decrease (second variable).

This understanding is rooted in statistical analysis, where correlation coefficients range from -1 to +1, with -1 indicating a perfect negative correlation. Thus, the emphatic link between the movement of one variable in opposition to another makes the choice about the relationship clear: an increase in one results in a decrease in the other.

Other options describe different types of relationships or states: a positive correlation would indicate both variables increase together, saying they are unrelated suggests no discernible pattern, and stating both remain constant does not capture the essence of correlation at all. These options do not align with the definition of a negative correlation coefficient, reinforcing the importance of the correct relationship interpretation.