Instruction 13-16
Given Below Are Results from the Regression Analysis

question 168

Multiple Choice

Instruction 13-16
Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy) and the independent variables are the age of the worker (Age) ,the number of years of education received (Edu) ,the number of years at the previous job (Job Yr) ,a dummy variable for marital status (Married: 1 = married,0 = otherwise) ,a dummy variable for head of household (Head: 1 = yes,0 = no) and a dummy variable for management position (Manager: 1 = yes,0 = no) .We shall call this Model 1.
$$\begin{array} { l r } \hline { \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.7035 \\\text { R Square } & 0.4949 \\\text { Adjusted R } & 0.4030 \\\text { Square } & \\\text { Standard } & 18.4861 \\\text { Error } \\\text { Observations } & 40 \\\hline\end{array}$$ ANOVA
$\begin{array}{lrrrrr}\hline & d f & { S S } & { M S } & F & \text { Significance } F \\\hline \text { Regression } & 6 & 11048.6415 & 1841.4402 & 5.3885 & 0.00057 \\\text { Residual } & 33 & 11277.2586 & 341.7351 & & \\\text { Total } & 39 & 22325.9 & & &\end{array}$

$\begin{array}{lrrrrrr} & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & 32.6595 & 23.18302 & 1.4088 & 0.1683 & -14.5067& 79.8257 \\\text { Age } & 1.2915 & 0.3599 & 3.5883 & 0.0011 & 0.5592 &2.0238 \\\text { Edu } & -1.3537 & 1.1766 & -1.1504 & 0.2582 & -3.7476 &1.0402\\\text { JobYr } & 0.6171 & 0.5940 & 1.0389 & 0.3064 & -0.5914 & 1.8257 \\\text { Married } & -5.2189 & 7.6068 & -0.6861 & 0.4974 & -20.6950 & 10.2571 \\\text { Head } & -14.2978 & 7.6479 & -1.8695 & 0.0704 & -29.8575 & 1.2618 \\\text { Manager } & -24.8203 & 11.6932 & -2.1226 & 0.0414 & -48.6102 & -1.0303\end{array}$ Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager.The results of the regression analysis are given below:
$$\begin{array} { l r } \hline{ \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.6391 \\\text { R Square } & 0.4085 \\\text { Adjusted R } & 0.3765 \\\text { Square } & \\\text { Standard Error } & 18.8929 \\\text { Observations } &40 \\\hline\end{array}$$ $$\begin{array}{l}\text { ANOVA }\\\begin{array} { l r r r l r } \hline & d f & { S S } & { M S } & F & \text { Significance } F \\\hline \text { Regression } & 2 & 9119.0897 & 4559.5448 & 12.7740 & 0.0000 \\\text { Residual } & 37 & 13206.8103 & 356.9408 & & \\\text { Total } & 39 & 22325.9 & & & \\\hline\end{array}\\\begin{array} { l r r r r } \hline & \text { Coefficients } & \text { Standard Error } & { t \text { Stat } } & P \text {-value } \\\hline \text { Intercept } & - 0.2143 & 11.5796 & - 0.0185 & 0.9853 \\\text { Age } & 1.4448 & 0.3160 & 4.5717 & 0.0000 \\\text { Manager } & - 22.5761 & 11.3488 & - 1.9893 & 0.0541 \\\hline\end{array}\end{array}$$
-Referring to Instruction 13-16 Model 1,which of the following is a correct statement?

• A)On average,those who are in a management position are estimated to stay jobless shorter by approximately 5.22 weeks,while holding constant the effects of all the remaining independent variables.
• B)On average,those who are in a management position are estimated to stay jobless shorter by approximately 14.30 weeks,while holding constant the effects of all the remaining independent variables.
• C)On average,those who are in a management position are estimated to stay jobless shorter by approximately 1.35 weeks,while holding constant the effects of all the remaining independent variables.
• D)On average,those who are in a management position are estimated to stay jobless shorter by approximately 24.82 weeks,while holding constant the effects of all the remaining independent variables.

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Definitions:

Economic Profits

The net amount left when a business subtracts its full range of costs, explicit and implicit, from its entire revenue.

New Market

An emerging or previously unexplored segment of an industry where a business can expand or introduce its products or services.

Repeated Game

A strategic scenario in game theory where the same game is played several times, allowing players to revise their strategy based on past outcomes.

Nash Equilibrium

A concept in game theory where each player's strategy is optimal given the strategies of all other players in the game, leading to a situation from which no player has an incentive to deviate.