Regression Line of Y on X:
The regression line of Y on X is given by the equation y = -2x + 3.

Regression Line of X on Y:
The regression line of X on Y is given by the equation 8x = -y + 3.

Correlation Coefficient:
The correlation coefficient, denoted by r, measures the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, where -1 indicates a perfect negative linear relationship, 1 indicates a perfect positive linear relationship, and 0 indicates no linear relationship.

To find the correlation coefficient between X and Y, we can use the formula:

r = √[(slope of regression line of Y on X) * (slope of regression line of X on Y)]

First, let's find the slope of the regression line of Y on X:
The equation of the regression line of Y on X is y = -2x + 3.
Comparing this equation with the general form y = mx + c, we can see that the slope of the regression line is -2.

Next, let's find the slope of the regression line of X on Y:
The equation of the regression line of X on Y is 8x = -y + 3.
Rearranging this equation to the general form, we get y = -8x + 3.
Comparing this equation with y = mx + c, we can see that the slope of the regression line is -8.

Now, we can calculate the correlation coefficient:
r = √[(-2) * (-8)]
r = √[16]
r = 4

Conclusion:
The coefficient of correlation between X and Y is 4. This indicates a strong positive linear relationship between the two variables.