What does Pearson's correlation coefficient measure?

Pearson's correlation coefficient is a statistical measure that reflects the strength and direction of a linear relationship between two variables. When you calculate this coefficient, you obtain a value ranging from -1 to +1. A value close to +1 indicates a strong positive linear relationship, meaning that as one variable increases, the other variable tends to also increase. Conversely, a value close to -1 suggests a strong negative linear relationship, where an increase in one variable is associated with a decrease in the other. A value near 0 indicates little to no linear correlation between the variables.

This metric is crucial in statistics because it not only shows whether a relationship exists but also how closely the two variables are related in a linear sense. The other options, while relevant in the context of data analysis and interpretation, do not pertain directly to the specific purpose of Pearson's correlation coefficient. For instance, averaging data points, measuring deviation from the mean, or counting frequency are different concepts entirely, focusing on different statistical aspects.