What does a correlation coefficient indicate?

A correlation coefficient is a statistical measure that indicates the strength and direction of a linear relationship between two variables. When the correlation coefficient is calculated, it yields a value ranging from -1 to 1. A value close to 1 signifies a strong positive relationship, meaning that as one variable increases, the other tends to increase as well. Conversely, a value close to -1 indicates a strong negative relationship, where one variable increases while the other decreases. A correlation coefficient near 0 suggests little to no linear relationship between the variables.

This measurement is fundamental in data analysis and helps researchers and analysts determine how changes in one variable are associated with changes in another. It provides insight into the nature of the relationship, which can inform decisions, predictions, and further analytics efforts.

Other options focus on different aspects of data analysis and modeling. For instance, the level of uncertainty in data would relate more to concepts like variance or standard deviation rather than correlation. The percentage of variance explained is related to regression analysis and the R-squared statistic, while overall accuracy of forecasts pertains to measures of forecast performance, such as mean absolute error or mean squared error.