16.32 Data are provided here with descriptive statistics, a correlation coefcient, and a regression equation: 7' = 0.426, 17 = 219.974 + 186.595(X). X Y 0.13 200.00 0.27 98.00 0.49 543.00 0.57 385.00 0.84 420.00 1.12 312.00 MX = 0.57 My = 326.333 SDX = 0.333 SDY = 145.752 Using this information, compute the following estimates of prediction error: a. Calculate the sum of squared errors for the mean, 3.9mm. b. Now, using the regression equation provided, calculate the sum of squared errors for the regression equation, 33...\"... c. Using your work, calculate the proportionate reduction in error for these data. d. Check that this calculation of r2 equals the square of the correlation coefcient. e. Compute the standard error of the estimate