A Statistician Estimated the Multiple Regression Model $y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \varepsilon$

A statistician estimated the multiple regression model $y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \varepsilon$ , with 45 observations. The computer output 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 l. Fill in the missing results (up to three decimal places). $$\begin{array} { | c | c c c | } \hline \text { Predictor } & \text { Coef } & \text { StDev } & \text { T } \\\hline \text { Constant } & \mathbf { 2 . 7 9 4 } & \boldsymbol { a } & 6.404 \\x _ { 1 } & \boldsymbol { b } & 0.007 & - 0.025 \\x _ { 2 } & 0.383 & 0.072 & c \\\hline\end{array}$$ S = d R-Sq = e. $$\begin{array}{l}\text { ANALYSIS OF VARIANCE }\\\begin{array} { | l | c c c c | } \hline \begin{array} { l } \text { Source of } \\\text { Variation }\end{array} & \mathrm { df } & \text { SS } & \text { MS } & \text { F } \\\hline \text { Regression } & f & i & j & l \\\text { Error } & \boldsymbol { g } & 11.884 & \boldsymbol { k } & \\\hline \text { Total } & h & 26.887 & & \\\hline\end{array}\end{array}$$