Question

please help with the attachment

X 12 6/2014 55 35 45 10 15 The estimated regression equation for these data is 9 - 62.25 -2.75x (a) Compute SSE, SST, and SSR using equations SSE 1-9), SST - DIY, -77%, and SSR-319,-7). SSE - SST - SSR- (b) Compute the coefficient of determination (Round your answer to three decimal places.) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The least squares ine provided a good ft as a large proportion of the variability in y has been explained by the least squares line. The least squares ine did not provide a good fit as a large proportion of the variability in y has been explained by the least squares Ine. The least squares line did not provide a good ft as a small proportion of the variability in y has been explained by the least squares Ine. The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. (c) Compute the sample correlation coefficient. (Round your answer to three decimal places.)

Answer 1

The output of regession analysis is

AD х Y SUMMARY OUTPUT 3 55 12 35 6 45 20 10 Regression Statistics Multiple F 0.959043 R Square 0.919764 Adjusted I 0.893018 Standard I 6.291529 Observati 5 14 15 ANOVA df 1 Regressio Residual Total SS MS F gnificance F 1361.25 1361.25 34.38947 0.009889 118.75 39.58333 1480 3 4 Coefficientsandard Err t Stat P-value Lower 95%Upper 95%ower 95.0%pper 95.00 Intercept 62.25 5.875837 10.59423 0.001797 43.55046 80.94954 43.55046 80.94954 -2.75 0.468943 -5.86425 0.009889 -4.24239 -1.25761 -4.24239 -1.25761

sola a ) SSE - 118.75 SST = 1480 SSR = 1361.25 b) 82 = 0.919 option :b) The least squares a good fit as line and did not provide a large proportion of variability explained by the least squares in y has been line. x = 0.959