Which of the following is a statistical tool used to describe the relationship between different data points?

The correlation coefficient is a statistical tool specifically designed to quantify the degree to which two variables are related. It provides insights into both the strength and direction of a relationship, ranging from -1 to +1. A value close to +1 indicates a strong positive correlation, meaning as one variable increases, the other also tends to increase. Conversely, a value close to -1 indicates a strong negative correlation, where one variable tends to decrease as the other increases. A value around 0 suggests little to no linear relationship between the variables.

While the other options—standard deviation, mean value, and linear regression—serve important roles in statistical analysis, they do not focus on describing relationships between data points in the same way. Standard deviation measures the dispersion of data points from the mean, mean value is a measure of central tendency, and linear regression is used to model the relationship between variables but goes beyond merely describing the relationship by providing an equation for prediction. The correlation coefficient stands out as the most direct measure of the relationship between different data points.