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

question 139

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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, which of the following is a correct statement? A)  37.65% of the total variation in the number of weeks a worker is unemployed due to a layoff can be explained by the age of the worker and whether the worker is a manager. B)  37.65% of the total variation in the number of weeks a worker is unemployed due to a layoff can be explained by the age of the worker and whether the worker is a manager After adjusting for the number of predictors and sample size. C)  37.65% of the total variation in the number of weeks a worker is unemployed due to a layoff can be explained by the age of the worker and whether the worker is a manager After adjusting for the level of significance D)  37.65% of the total variation in the number of weeks a worker is unemployed due to a layoff can be explained by the age of the worker and whether the worker is a manager Holding constant the effect of all the independent 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, which of the following is a correct statement?

Assess the influence of various factors (e.g., age of separation, individual attention, and environmental stimulation) on children's development.
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Definitions:

Fluid Intelligence

The capacity to reason and solve new problems independently of previously acquired knowledge.

Crystallized Intelligence

The ability to use skills, knowledge, and experience, often considered to improve with age.

Stereotype Threat

The risk of confirming negative stereotypes about one's group, which can hinder performance.

Intelligence Quotient

A score derived from standardized tests designed to assess human intelligence.

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