In Any Production Process in Which One or More Workers $( y )$

In any production process in which one or more workers are engaged in a variety of tasks, the total time spent in production varies as a function of the size of the workpool and the level of output of the various activities. In a large metropolitan department store, it is believed that the number of man-hours worked $( y )$ per day by the clerical staff depends on the number of pieces of mail processed per day $\left( x _ { 1 } \right)$ and the number of checks cashed per day $\left( x _ { 2 } \right)$ . Data collected for $n = 20$ working days were used to fit the model:
$$E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 }$$
A partial printout for the analysis follows:
Parameter Estimates
$\begin{array} { l r r r r r r } & & \text { PARAMETER } & \text { STANDARD } & \text { T FOR 0: } \\ \text { VARIABLE } & \text { DF } & \begin{array} { r } \text { ESTIMATE } \end{array} & \begin{array} { r } \text { T FRROR } \end{array} & \text { PARAMETER = 0 } & \text { PROB } > | T | \\ & & & & & \\ \text { INTERCEPT } & 1 & 114.420972 & 18.6848744 & 6.124 & 0.0001 \\ \text { X1 } & 1 & - 0.007102 & 0.00171375 & - 4.144 & 0.0007 \\ \text { X2 } & 1 & 0.037290 & 0.02043937 & 1.824 & 0.0857 \end{array}$
Calculate a $95 \%$ confidence interval for $\beta _ { 1 }$ .
A) $- .007 \pm .0036$
B) $- .007 \pm .0017$
C) $- .007 \pm .0007$
D) $- 4.144 \pm .0007$