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 ( x1) and the number of checks cashed per day (x2). data collected for n = 20 working days were used to fit the model: e(y) = β0 + β1x1 + β2x2 a partial printout for the analysis follows: parameter estimates variable df parameter estimate standard error t for 0: parameter = 0 prob > |t| intercept 1 114.420972 18.6848744 6.124 0.0001 x1 1 -0.007102 0.00171375 -4.144 0.0007 x2 1 0.037290 0.02043937 1.824 0.0857 calculate a 95% confidence interval for β1.