The correct answer is: B. Can be either negative or positive.
The correlation coefficient measures the strength and direction of the linear relationship between two variables. A positive correlation coefficient indicates that the two variables are positively correlated, meaning that as one variable increases, the other variable also tends to increase. A negative correlation coefficient indicates that the two variables are negatively correlated, meaning that as one variable increases, the other variable tends to decrease.
The slope of the regression line is a measure of the strength of the linear relationship between two variables. The slope of the regression line is positive if the two variables are positively correlated, and the slope of the regression line is negative if the two variables are negatively correlated. However, the slope of the regression line can be zero even if the two variables are correlated. This can happen if the relationship between the two variables is not linear.
For example, let’s say we want to find the relationship between height and weight. We might find that there is a positive correlation between height and weight, meaning that taller people tend to weigh more. However, the relationship between height and weight is not linear. Taller people do not weigh twice as much as shorter people. Therefore, the slope of the regression line would be positive, but it would not be equal to 2.
In conclusion, the correlation coefficient and the slope of the regression line are two different measures of the relationship between two variables. The correlation coefficient measures the strength and direction of the linear relationship, while the slope of the regression line measures the strength of the relationship. The correlation coefficient can be either positive or negative, while the slope of the regression line can be positive, negative, or zero.