The correlation coefficient, \( r \), is the slope of the "best-fit" line. FALSE TRUE

While it’s a common misconception, the correlation coefficient \( r \) is not the slope of the best-fit line; rather, it measures the strength and direction of a linear relationship between two variables. The slope of the best-fit line is calculated separately using the least squares method and reflects how much \( Y \) changes for a unit change in \( X \). So, while there's a connection between the two, they're not the same thing! In practical terms, understanding this distinction can prevent confusion when interpreting data in fields such as social sciences, finance, or even sports analytics! By knowing that \( r \) reflects correlation and not causation, you can more effectively assess data trends and make informed decisions without jumping to conclusions about cause-and-effect relationships.