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TABLE 13-17 Given Below Are Results from the Regression Analysis Where the Where

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TABLE 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), 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.
TABLE 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), 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.         Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given below:        -Referring to Table 13-17 Model 1, there is sufficient evidence that being married or not makes a difference in the mean number of weeks a worker is unemployed due to a layoff, while holding constant the effect of all the other independent variables at a 10% level of significance.
TABLE 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), 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.         Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given below:        -Referring to Table 13-17 Model 1, there is sufficient evidence that being married or not makes a difference in the mean number of weeks a worker is unemployed due to a layoff, while holding constant the effect of all the other independent variables at a 10% level of significance.
Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given below:
TABLE 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), 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.         Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given below:        -Referring to Table 13-17 Model 1, there is sufficient evidence that being married or not makes a difference in the mean number of weeks a worker is unemployed due to a layoff, while holding constant the effect of all the other independent variables at a 10% level of significance.
TABLE 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), 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.         Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given below:        -Referring to Table 13-17 Model 1, there is sufficient evidence that being married or not makes a difference in the mean number of weeks a worker is unemployed due to a layoff, while holding constant the effect of all the other independent variables at a 10% level of significance.
-Referring to Table 13-17 Model 1, there is sufficient evidence that being married or not makes a difference in the mean number of weeks a worker is unemployed due to a layoff, while holding constant the effect of all the other independent variables at a 10% level of significance.


Definitions:

Opening Inventory

The value of a business's inventory at the start of an accounting period.

NCI Share

Non-Controlling Interest Share, representing the portion of equity in a subsidiary not attributable directly to the parent company owners.

Intragroup Transactions

Deals or exchanges of goods, services, or funds between entities under the same parent company, often used for transferring resources within a corporate group.

NCI Share

The portion of equity (net assets) in a subsidiary not attributable, directly or indirectly, to the parent company, also known as non-controlling interest share.

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