Final answer:
The correlation coefficient, denoted as r, measures the strength of the linear relationship between two variables X and Y, ranging from -1 to +1. It is the indicator of how closely data in a scatterplot falls along a straight line.
Step-by-step explanation:
The measure that tells us the strength of the linear relationship between X and Y is the correlation coefficient, often denoted as r. The correlation coefficient ranges from -1 to +1, where a value of +1 indicates a perfect positive linear relationship, a value of -1 indicates a perfect negative linear relationship, and a value of 0 suggests no linear relationship at all.
The closer the number is to 1 or -1, the stronger is the linearity between the two variables. A positive r value indicates that as X increases, Y also increases, and similarly, a negative r value indicates that as X increases, Y decreases.
The coefficient of determination, r², is the square of the correlation coefficient and gives the proportion of the variance in the dependent variable that is predictable from the independent variable. While it is related to the correlation coefficient, it does not directly measure the strength of the linear relationship.