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SCENARIO 17-10 Given Below Are Results from the Regression Analysis 1=1 =

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SCENARIO 17-10 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=1 = married, 0=0 = otherwise), a dummy variable for head of household (Head: 1=1 = yes, 0=0 = no) and a dummy variable for management position (Manager: 1=1 = yes, 0=0 = no). We shall call this Model 1. The coefficient of partial determination ( Ry2R _ { \mathrm { y } } ^ { 2 } (All raiables excopt jj ) ) of each of the 6 predictors are, respectively, 0.28070.2807 , 0.0386,0.0317,0.0141,0.09580.0386,0.0317,0.0141,0.0958 , and 0.12010.1201 .

 Regression Statistics  Multiple R 0.7035 R Square 0.4949 Adjusted R 0.4030 Square  Standard 18.4861 Error  Observations 40\begin{array}{lr}\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 \text { ANOVA }
 SCENARIO 17-10 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. The coefficient of partial determination (  R _ { \mathrm { y } } ^ { 2 }  (All raiables excopt  j  ) ) of each of the 6 predictors are, respectively,  0.2807 ,  0.0386,0.0317,0.0141,0.0958 , and  0.1201 .   \begin{array}{lr} \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}    \text { ANOVA }       \begin{array}{l} \begin{array} { l r r r r r r }  \hline & \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 { Job Yr } & 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 \\ \hline \end{array} \end{array}  -Referring to Scenario 17-10 Model 1, there is sufficient evidence that the number of weeks a worker is unemployed due to a layoff depends on at least one of the explanatory variables at a 10% level of significance.


 Coefficients  Standard Error t Stat  P-value  Lower 95%  Upper 95%  Intercept 32.659523.183021.40880.168314.506779.8257 Age 1.29150.35993.58830.00110.55922.0238 Edu 1.35371.17661.15040.25823.74761.0402 Job Yr 0.61710.59401.03890.30640.59141.8257 Married 5.21897.60680.68610.497420.695010.2571 Head 14.29787.64791.86950.070429.85751.2618 Manager 24.820311.69322.12260.041448.61021.0303\begin{array}{l}\begin{array} { l r r r r r r } \hline & \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 { Job Yr } & 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 \\\hline\end{array}\end{array}
-Referring to Scenario 17-10 Model 1, there is sufficient evidence that the
number of weeks a worker is unemployed due to a layoff depends on at least one of the
explanatory variables at a 10% level of significance.


Definitions:

Duopoly

A market structure dominated by two companies, resulting in limited competition.

Demand Curve

A chart depicting how the price of an item correlates with the amount of that item consumers are ready and capable of buying at different price levels.

Marginal Cost

The extra cost involved in producing one more unit of a product or service.

Cartel

An association of independent companies or organizations formed to control production, pricing, and marketing of goods to suppress competition.

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