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The Computer Output for the Multiple Regression Model y:β0+β1x1+β2x2+εy : \beta _ { 0 }+ \beta _ { 1 }x_ { 1 }+ \beta _ { 2 }x_ { 2 }+ε

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The computer output for the multiple regression model y:β0+β1x1+β2x2+εy : \beta _ { 0 }+ \beta _ { 1 }x_ { 1 }+ \beta _ { 2 }x_ { 2 }+ε is shown below. However, because of a printer malfunction some of the results are not shown. These are indicated by the boldface letters a to i. Fill in the missing results (up to three decimal places).  predictor  Coef 5DsvT Constant a6.154.11π13.51b1.25x20.710.30c\begin{array} { | c | c c c | } \hline \text { predictor } & \text { Coef } & \mathbf { 5 } \mathrm { D } _ { \mathbf { s } } \boldsymbol { v } & \boldsymbol { T } \\\hline \text { Constant } & \boldsymbol { a } & \mathbf { 6 . 1 5 } & 4.11 \\\boldsymbol { \pi } _ { 1 } & 3.51 & \boldsymbol { b } & 1.25 \\\boldsymbol { x } _ { 2 } & - 0.71 & 0.30 & \boldsymbol { c } \\\hline\end{array} S=d R-Sq =eS = d \quad \text { R-Sq } = e ANALYSIS OF VARIANCE
 Source of Variation d5MSF Repression 2412Ei Error 37fH Total 39974\begin{array} { | l | c c c c | } \hline \text { Source of Variation } & \boldsymbol { d } & \mathbf { 5 } & \boldsymbol { M S } & \boldsymbol { F } \\\hline \text { Repression } & 2 & 412 & \boldsymbol { E } & \boldsymbol { i } \\\text { Error } & 37 & \boldsymbol { f } & \boldsymbol { H } & \\\hline \text { Total } & 39 & 974 & & \\\hline\end{array}


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