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urmber of weeks a worker is unerriployed due to a layoir (Onempioy) and Giveri below are resuits fromi the dummy variable for management position (Manager: 1= yes, 0 = no). The results of the regression analysis are given below. regression analysis wriere trhe dependent employed due layoir (Unermiploy) pendent vanabies are the age of the worker (Age) and E Click the icon to view the results. Determine whether the following statement is true or false: There is sufficient evidence that age has an effect on the number of weeks a worker is unemployed due to a layoff while holding constant the effect of the other independ variable at a 10% level of significance. - X Regression Statistics False O True Regression Statistics Multiple R 0.6391 RSquare 0.4085 Adjusted R Square 0.3765 Standard Error 18.8929 Observations 40 ANOVA df SS MS Significance F Regression 9119.0897 4559.5448 12.7740 0.0000 Residual 37 13206.8103 356.9408 Total 39 22325.9 Standard Error P-value t Stat -0.0185 Coefficients Intercept -0.2143 11.5796 0.9853 Age Manager 1.4448 0.3160 4.5717 0.0000 -22.5761 11.3488 -1.9893 0.0541

urmber of weeks a worker is unerriployed due to a layoir (Onempioy) and Giveri below are resuits fromi the dummy variable for management position (Manager: 1= yes, 0 = no). The results of the regression analysis are given below. regression analysis wriere trhe dependent employed due layoir (Unermiploy) pendent vanabies are the age of the worker (Age) and E Click the icon to view the results. Determine whether the following statement is true or false: There is sufficient evidence that age has an effect on the number of weeks a worker is unemployed due to a layoff while holding constant the effect of the other independ variable at a 10% level of significance. - X Regression Statistics False O True Regression Statistics Multiple R 0.6391 RSquare 0.4085 Adjusted R Square 0.3765 Standard Error 18.8929 Observations 40 ANOVA df SS MS Significance F Regression 9119.0897 4559.5448 12.7740 0.0000 Residual 37 13206.8103 356.9408 Total 39 22325.9 Standard Error P-value t Stat -0.0185 Coefficients Intercept -0.2143 11.5796 0.9853 Age Manager 1.4448 0.3160 4.5717 0.0000 -22.5761 11.3488 -1.9893 0.0541

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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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. Click the icon to view the results. Determine whether the following statement is true or false: There is sufficient evidence that age has an effect on the number of weeks a worker is unemployed due to a layoff while holding constant the effect of the other independent variable at a 10% level of significance. Regression Statistics False True 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 Significance F Regression 2 9119.0897 4559.5448 12.7740 0.0000 Residual 37 13206.8103 356.9408 Total 39 22325.9 Coefficients Standard Error t Stat P-value Intercept -0.2143 11.5796 -0.0185 0.9853 Age 1.4448 0.3160 4.5717 0.0000 Manager -22.5761 11.3488 -1.9893 0.0541
Transcribed Image Text: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. Click the icon to view the results. Determine whether the following statement is true or false: There is sufficient evidence that age has an effect on the number of weeks a worker is unemployed due to a layoff while holding constant the effect of the other independent variable at a 10% level of significance. Regression Statistics False True 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 Significance F Regression 2 9119.0897 4559.5448 12.7740 0.0000 Residual 37 13206.8103 356.9408 Total 39 22325.9 Coefficients Standard Error t Stat P-value Intercept -0.2143 11.5796 -0.0185 0.9853 Age 1.4448 0.3160 4.5717 0.0000 Manager -22.5761 11.3488 -1.9893 0.0541
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