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

question 126

Essay

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)( y ) per day by the clerical staff depends on the number of pieces of mail processed per day (x1)\left( x _ { 1 } \right) and the number of checks cashed per day (x2)\left( x _ { 2 } \right) . Data collected for n=20n = 20 working days were used to fit the model:
E(y)=β0+β1x1+β2x2E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 }
A printout for the analysis follows:
 Analysis of Variance  SOURCE  DF  SS  MS  F VALUE  PROB > F 27089.065123544.5325613.2670.0003 MODEL 174541.72142267.16008 ERROR 1911630.78654\begin{array}{lrrrrr}\hline & {\text { Analysis of Variance }} \\& & & & \\\text { SOURCE } & \text { DF } & \text { SS } & \text { MS } & \text { F VALUE } & \text { PROB > F } \\& 2 & 7089.06512 & 3544.53256 & 13.267 & 0.0003 \\\text { MODEL } & 17 & 4541.72142 & 267.16008 & & \\\text { ERROR } & 19 & 11630.78654 & & &\end{array}

 ROOT MSE 16.34503 R-SQUARE 0.6095 DEP MEAN 93.92682 ADJ R-SQ 0.5636 C.V. 17.40188\begin{array}{llll}\text { ROOT MSE } & 16.34503 & \text { R-SQUARE } & 0.6095 \\\text { DEP MEAN } & 93.92682 & \text { ADJ R-SQ } & 0.5636 \\\text { C.V. } & 17.40188 & &\end{array}

 PARAMETER  STANDARD  T FOR 0:  VARIABLE  DF  ESTIMATE  ERROR  PARAMETER =0 PROB >T INTERCEPT 1114.42097218.68485744 X1 10.0071020.001713756.1240.0001 X2 10.0372900.020439374.1440.00071.8240.0857\begin{array}{lrrrrr} & \text { PARAMETER } & \text { STANDARD } & \text { T FOR 0: } & \\\text { VARIABLE } & \text { DF } & \text { ESTIMATE } & \text { ERROR } & \text { PARAMETER }=0 & \text { PROB }>|\mathrm{T}| \\\text { INTERCEPT } & 1 & 114.420972 & 18.68485744 & & \\\text { X1 } & 1 & -0.007102 & 0.00171375 & 6.124 & 0.0001 \\\text { X2 } & 1 & 0.037290 & 0.02043937 & -4.144 & 0.0007 \\& & 1.824 & 0.0857\end{array}

 OBS  X1  X2  Actual  Value  Predict  Value  Residual  Lower 95% CL  Predict  Upper 95% CL  Predict 778164474.70783.1758.46847.224119.126\begin{array}{rrrrrrrr}\text { OBS } & \text { X1 } & \text { X2 } & \begin{array}{r}\text { Actual } \\\text { Value }\end{array} & \begin{array}{r}\text { Predict } \\\text { Value }\end{array} & \text { Residual } & \begin{array}{r}\text { Lower 95\% CL } \\\text { Predict }\end{array} & \begin{array}{r}\text { Upper 95\% CL } \\\text { Predict }\end{array} \\\hline & 7781 & 644 & 74.707 & 83.175 & -8.468 & 47.224 & 119.126 \\\hline\end{array}

Test to determine if there is a positive linear relationship between the number of man-hours worked, yy , and the number of checks cashed per day, x2x _ { 2 } . Use α=.05\alpha = .05 .


Definitions:

Holding Cost

The expenses associated with storing unsold goods or materials, including warehousing, insurance, depreciation, and opportunity cost.

Shipping Cost

The expense incurred to transport goods from one location to another.

Factor Weighting Technique

A decision-making tool that assigns weights to various factors or criteria based on their importance, used to evaluate alternatives or make choices.

Subjectivity

The quality of being based on or influenced by personal feelings, tastes, or opinions rather than external facts or evidence.

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