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SCENARIO 14-17
Given Below Are Results from the Regression Analysis

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SCENARIO 14-17
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) and a dummy variable for management position (Manager: 1 = yes, 0 = no).
The results of the regression analysis are given below:   Regression Statistics  Multiple R 0.6391 R Square 0.4085 Adjusted R Square 0.3765 Standard Error 18.8929 Observations 40\begin{array}{l}\hline \ { \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.6391 \\\text { R Square } & 0.4085 \\\text { Adjusted R Square } & 0.3765 \\\text { Standard Error } & 18.8929 \\\text { Observations } & 40 \\\hline\end{array}

 ANOVA \text { ANOVA }
 SCENARIO 14-17 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) and a dummy variable for management position (Manager: 1 = yes, 0 = no). The results of the regression analysis are given below:  \begin{array}{l} \hline \ { \text { Regression Statistics } } \\ \hline \text { Multiple R } & 0.6391 \\ \text { R Square } & 0.4085 \\ \text { Adjusted R Square } & 0.3765 \\ \text { Standard Error } & 18.8929 \\ \text { Observations } & 40 \\ \hline \end{array}    \text { ANOVA }       \begin{array} { l r r r r }  \hline & \text { Coefficients } & \text { Standard Error } & { t \text { Stat } } &  { \text { P-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}  -Referring to Scenario 14-17, the alternative hypothesis  H _ { 1 } : \text { At least one of } \beta _ { j } \neq 0 \text { for } j = 1,2  implies that the number of weeks a worker is unemployed due to a layoff is related to all of the explanatory variables.


 Coefficients  Standard Error t Stat  P-value  Intercept 0.214311.57960.01850.9853 Age 1.44480.31604.57170.0000 Manager 22.576111.34881.98930.0541\begin{array} { l r r r r } \hline & \text { Coefficients } & \text { Standard Error } & { t \text { Stat } } & { \text { P-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}
-Referring to Scenario 14-17, the alternative hypothesis H1: At least one of βj0 for j=1,2H _ { 1 } : \text { At least one of } \beta _ { j } \neq 0 \text { for } j = 1,2 implies that the number of weeks a worker is unemployed due to a layoff is related to all of the
explanatory variables.


Definitions:

Arthralgia

Pain in a joint.

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Pertaining to the cartilage and ribs, often used to describe the connection between rib cartilage and the ribs themselves.

Cost

The amount of money required to purchase something or the expenditure incurred by a business in producing goods or services.

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The body's protective response to injury or damage, marked by redness, heat, swelling, and pain, aimed at eliminating harmful stimuli and initiating healing.

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