What does a negative correlation coefficient indicate?

A negative correlation coefficient indicates that as one variable increases, the other variable decreases. This relationship demonstrates an inverse association between the two variables being measured. For example, if we were studying the relationship between hours spent studying and the number of errors made on an exam, a negative correlation would suggest that as study hours increase, the number of errors typically decreases.

This makes the understanding of correlation crucial in interpreting statistical data, as it allows researchers and analysts to predict how changes in one variable may impact another. The strength of this negative relationship is quantified by the numerical value of the correlation coefficient, where values closer to -1 indicate a stronger negative correlation.

In contrast to this, the other options describe different types of relationships. The first option suggests a positive correlation, which indicates that both variables move in the same direction. The second option implies no relationship at all, which would correspond to a correlation coefficient close to 0. Lastly, the last option refers to independence, which means that the variables do not affect each other at all, again closely related to a correlation coefficient of 0. Thus, a negative correlation coefficient specifically highlights an inverse relationship between the two variables.