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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, ________ of the variation in the number of weeks a worker is unemployed due to a layoff can be explained by the age of the worker while controlling for the other independent variables.


 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, ________ of the variation in the number of weeks a
worker is unemployed due to a layoff can be explained by the age of the worker while controlling
for the other independent variables.

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Stapes

A small, stirrup-shaped bone in the middle ear that plays a key role in transmitting sound vibrations to the inner ear.

Bony Labyrinth

A complex system of channels and cavities within the temporal bone of the skull, housing the organs of hearing and balance.

Oval Window

The beginning of the inner ear.

Vestibule

An entrance or enclosed anteroom leading to a larger space, often found in buildings or anatomical structures.

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