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SCENARIO 13-17
Given Below Are Results from the Regression Analysis

question 159

True/False

SCENARIO 13-17
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 ANOVA  df  SS  MS  F  Significance F Regression 29119.08974559.544812.77400.0000 Residual 3713206.8103356.9408 Total 3922325.9 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}\begin{array} { l r } \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 r } \hline &{ \text { df } } & { \text { SS } } & { \text { MS } } &{ \text { 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 SCENARIO 13-17, there is sufficient evidence that at least one of the explanatory variables is related to the number of weeks a worker is unemployed due to a layoff at a 10% level of significance.

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Definitions:

Competency-Based Pay

A compensation approach that ties an employee's pay to their level of competency or skills, rather than their job title or position.

Advantages and Disadvantages

The beneficial and unfavorable aspects or outcomes of a decision, action, or situation.

Wage-Rate Compression

A situation where differences in wages among employees narrow, often leading to less distinction in pay between higher and lower-level jobs.

Compensation Difference

The variation in pay and benefits among employees, which can be due to factors like experience, education, job function, or performance.

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