(Solved): The following estimated regression equation based on 30 observations was presented. \[ \varphi=17.6 ...

The following estimated regression equation based on 30 observations was presented. \[ \varphi=17.6+3.8 x_{1}-2.3 x_{2}+7.6 x_{3}+2.7 x_{4} \] The values of \( 5 S T \) and \( S 5 R \) are 1,807 and 1,751, respectively. (a) Compute \( R^{2} \). (Round your answer to three decimal places.) \[ R^{2}= \] (b) Compute \( R_{e}^{2} \). (Round your answer to three decimal places.) \[ R_{e}{ }^{2}= \] (c) Comment on the goodness of fit. (for purposes of this exercise, consider a proportion large if it is at least \( 0.55 \). ) The estimated regression equation provided a good fit as a smail proportion of the variabilty in \( y \) has been explained by the estimated regression equation. The estimated regression equation did not provide a good fit as a large proportion of the variability in \( y \) has been explained by the estimated regression equation. The estimated regression equation provided a good fit as a large proportion of the variability in \( y \) has been explained by the estimated regression equation. The estimated regression equation did not provide a good fit as a smalhioportion of the variability in \( y \) has been explained by the estimated regression equation. The following estimated regression equation based on 30 observations was presented. \[ y=17.6+3.8 x_{1}-2.3 x_{2}+7.6 x_{3}+2.7 x_{4} \] The values of \( S S T \) and \( S S R \) are 1,807 and 1,751 , respectively. (a) Compute \( R^{2} \). (Round your answer to three decimal places.) \[ R^{2}= \] (b) Compute \( R_{a}{ }^{2} \). (Round your answer to three decimal places.) \[ R_{a}^{2}= \] (c) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least \( 0.55 \). ) The estimated regression equation provided a good fit as a small proportion of the variability in \( y \) has been \( e \) regression equation. The estimated regression equation did not provide a good fit as a large proportion of the variability in \( y \) has t regression equation. The estimated reqression equation provided a aood fit as a larae proportion of the variability in \( y \) has been es \[ y=17.6+3.8 x_{1}-2.3 x_{2}+7.6 x_{3}+2.7 x_{4} \] The values of \( S S T \) and SSR are 1,807 and 1,751 , respectively. (a) Compute \( R^{2} \). (Round your answer to three decimal places,) \[ R^{2}= \] (b) Compute \( R_{a}{ }^{2} \). (Round your answer to three decimal places.) \[ R_{s}{ }^{2}= \] (c) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least \( 0.55 \).) The estimated regression equation provided a good fit as a small proportion of the variability in \( y \) has been explained by the estimated regression equation. The estimated regression equation did not provide a good fit as a large proportion of the variability in \( y \) has been explained by the estimated regressian equation. The estimated regression equation provided a good fit as a large proportion of the variability in \( y \) has been explained by the estimated regression equation. The estimated regression equation did not provide a good fit as a small proportion of the variability in \( y \) has been explained by the estimated regression equation.