Final answer:
The correlation coefficient is preferred over covariance because it provides a standardized measure of the strength and direction of the relationship between two variables. It ranges from -1 to 1, making it easier to interpret. The correlation coefficient allows for comparisons between different pairs of variables because it is unitless.
Step-by-step explanation:
The correlation coefficient is preferred over covariance because it provides a standardized measure of the strength and direction of the relationship between two variables. Unlike covariance, which is measured in units of the variables being analyzed, the correlation coefficient ranges from -1 to 1, making it easier to interpret. A correlation coefficient of 1 indicates a perfect positive relationship, -1 indicates a perfect negative relationship, and 0 indicates no relationship between the variables.
For example, if we were analyzing the relationship between studying time and exam scores, a correlation coefficient of 0.9 would indicate a strong positive relationship, meaning that as studying time increases, exam scores also increase. On the other hand, a correlation coefficient of -0.5 would indicate a moderate negative relationship, suggesting that as studying time increases, exam scores decrease.
Additionally, the correlation coefficient allows for comparisons between different pairs of variables because it is unitless. This makes it useful for comparing relationships across different data sets or studies.