A study provides data on variables that may be related to the number of weeks a manufacturing worker has been jobless. The dependent variable in the study (Weeks) was defined as the number of weeks a worker has been jobless due to a layoff. The following independent variables were used in the study.   Age                 The age of the worker Educ                The number of years of education Married           A dummy variable; 1 if married, 0 otherwise Head                A dummy variable; 1 if head of household, 0 otherwise Tenure             The number of years on the previous job Manager          A dummy variable; 1 if management occupation, 0 otherwise Sales               A dummy variable; 1 if sales occupation, 0 otherwise   The data are available in the file named Layoffs.MTW.   Develop an estimated regression equation that can be used to predict the number of weeks a worker has been jobless due to a layoff given age, education and marital status of the worker. Develop an estimated regression equation that can be used to predict the number of weeks a worker has been jobless due to a layoff given age, education, marital status and the number of years on the previous job of the worker. Does the addition of the variable in part (b) add significant benefit to the model? Why or why not? Weeks Age Educ Married Head Tenure Manager Sales 37 30 14 1 1 1 0 0 62 27 14 1 0 6 0 0 49 32 10 0 1 11 0 0 73 44 11 1 0 2 0 0 8 21 14 1 1 2 0 0 15 26 13 1 0 7 1 0 52 26 15 1 0 6 0 0 72 33 13 0 1 6 0 0 11 27 12 1 1 8 0 0 13 33 12 0 1 2 0 0 39 20 11 1 0 1 0 0 59 35 7 1 1 6 0 0 39 36 17 0 1 9 1 0 44 26 12 1 1 8 0 0 56 36 15 0 1 8 0 0 31 38 16 1 1 11 0 1 62 34 13 0 1 13 0 0 25 27 19 1 0 8 0 0 72 44 13 1 0 22 0 0 65 45 15 1 1 6 0 0 44 28 17 0 1 3 0 1 49 25 10 1 1 1 0 0 80 31 15 1 0 12 0 0 7 23 15 1 0 2 0 0 14 24 13 1 1 7 0 0 94 62 13 0 1 8 0 0 48 31 16 1 0 11 0 0 82 48 18 0 1 30 0 0 50 35 18 1 1 5 0 0 37 33 14 0 1 6 0 1 62 46 15 0 1 6 0 0 37 35 8 0 1 6 0 0 40 32 9 1 1 13 0 0 16 40 17 1 0 8 1 0 34 23 12 1 1 1 0 0 4 36 16 0 1 8 0 1 55 33 12 1 0 10 0 1 39 32 16 0 1 11 0 0 80 62 15 1 0 16 0 1 19 29 14 1 1 12 0 0 98 45 12 1 0 17 0 0 30 38 15 0 1 6 0 1 22 40 8 1 1 16 0 1 57 42 13 1 0 2 1 0 64 45 16 1 1 22 0 0 22 39 11 1 1 4 0 0 27 27 15 1 0 10 0 1 20 42 14 1 1 6 1 0 30 31 10 1 1 8 0 0 23 33 13 1 1 8 0 0