Regression Analysis: Calculating Sum of Squared Residuals

To find the sum of squared residuals in the regression of C on D, we need to calculate the residuals and sum their squares.

The regression equation for C on D is: C = a + bD

Since the regression coefficient (slope) for D in the regression of C on D is 0.8, the equation becomes: C = a + 0.8D

To find the residuals, we subtract the predicted values of C from the actual values of C.

Residuals = C - (a + 0.8D)

Since the mean of C is zero and the regression equation is C = a + 0.8D, the predicted value of C is also zero when D is zero. Therefore, we have:

Residuals = C - (0 + 0.8D) = C - 0.8D

Now, we need to calculate the sum of squared residuals.

Sum of squared residuals = ∑[(C - 0.8D)^2]

Since there are 21 observations, we need to sum the squared residuals for all 21 observations.

Therefore, the sum of squared residuals in the regression of C on D is:

Sum of squared residuals = ∑[(C - 0.8D)^2] for i = 1 to 21

Note that we don't have enough information to determine the actual values of C, D, or Y, so we cannot calculate the sum of squared residuals without further information.