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Instruction 16-6
Given Below Are Results from the Regression Analysis

question 30

Short Answer

Instruction 16-6
Given below are results from the regression analysis on 40 observations where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Y) and the independent variables are the age of the worker (X1), the number of years of education received (X2), the number of years at the previous job (X3), a dummy variable for marital status (X4: 1 = married, 0 = otherwise), a dummy variable for head of household (X5: 1 = yes, 0 = no) and a dummy variable for management position (X6: 1 = yes, 0 = no).
The coefficient of multiple determination (R2j) the regression model using each of the 6 variables Xj as the dependent variable and all other X variables as independent variables are, respectively, 0.2628, 0.1240, 0.2404, 0.3510, 0.3342 and 0.0993.
The partial results from best-subset regression are given below:
 Model  R Square  Adj. R Square  Std. Error X1X5X60.45680.411618.3534X1X2X5X60.46970.409118.3919X1X3X5X60.46910.408418.4023X1X2X3X5X60.48770.412318.3416X1X2X3X4X5X60.49490.403018.4861\begin{array} { | l | l | l | l | } \hline \text { Model } & \text { R Square } & \text { Adj. R Square } & \text { Std. Error } \\\hline X _ { 1 } X _ { 5 } X _ { 6 } & 0.4568 & 0.4116 & 18.3534 \\\hline X _ { 1 } X _ { 2 } X _ { 5 } X _ { 6 } & 0.4697 & 0.4091 & 18.3919 \\\hline X _ { 1 } X _ { 3 } X _ { 5 } X _ { 6 } & 0.4691 & 0.4084 & 18.4023 \\\hline X _ { 1 } X _ { 2 } X _ { 3 } X _ { 5 } X _ { 6 } & 0.4877 & 0.4123 & 18.3416 \\\hline X _ { 1 } X _ { 2 } X _ { 3 } X _ { 4 } X _ { 5 } X _ { 6 } & 0.4949 & 0.4030 & 18.4861 \\\hline\end{array}
-Referring to Instruction 16-6,what is the value of the variance inflationary factor of Manager?

Calculate and interpret the total, average, and marginal costs in various business conditions.
Understand the concept of average total, variable, and fixed costs.
Calculate total variable and total costs based on average costs.
Recognize economies and diseconomies of scale in production.

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