Solved

To Examine the Differences Between Salaries of Male and Female

Question 107

Multiple Choice

To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) ,
Educ = the number of years of education,
Exper = the number of months of experience,
Train = the number of weeks of training,
Gender = the gender of an individual; 1 for males, and 0 for females.
Excel partial outputs corresponding to these models are available and shown below.
Model A: Salary = β0 + β1Educ + β2Exper + β3Train + β4Gender + ε To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Using Model B, what is the regression equation for males? A) = 4,713.26 + 139.5366Educ + 3.3488Exper + 609.25Gender B) = 5,322.51 + 139.5366Educ + 3.3488Exper C) = 4,713.26 + 139.5366Educ + 3.3488Exper D) = 4,663.31 + 140.6634Educ + 3.3566Exper Model B: Salary = β0 + β1Educ + β2Exper + β3Gender + ε To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Using Model B, what is the regression equation for males? A) = 4,713.26 + 139.5366Educ + 3.3488Exper + 609.25Gender B) = 5,322.51 + 139.5366Educ + 3.3488Exper C) = 4,713.26 + 139.5366Educ + 3.3488Exper D) = 4,663.31 + 140.6634Educ + 3.3566Exper Using Model B, what is the regression equation for males?


A) To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Using Model B, what is the regression equation for males? A) = 4,713.26 + 139.5366Educ + 3.3488Exper + 609.25Gender B) = 5,322.51 + 139.5366Educ + 3.3488Exper C) = 4,713.26 + 139.5366Educ + 3.3488Exper D) = 4,663.31 + 140.6634Educ + 3.3566Exper = 4,713.26 + 139.5366Educ + 3.3488Exper + 609.25Gender
B) To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Using Model B, what is the regression equation for males? A) = 4,713.26 + 139.5366Educ + 3.3488Exper + 609.25Gender B) = 5,322.51 + 139.5366Educ + 3.3488Exper C) = 4,713.26 + 139.5366Educ + 3.3488Exper D) = 4,663.31 + 140.6634Educ + 3.3566Exper = 5,322.51 + 139.5366Educ + 3.3488Exper
C) To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Using Model B, what is the regression equation for males? A) = 4,713.26 + 139.5366Educ + 3.3488Exper + 609.25Gender B) = 5,322.51 + 139.5366Educ + 3.3488Exper C) = 4,713.26 + 139.5366Educ + 3.3488Exper D) = 4,663.31 + 140.6634Educ + 3.3566Exper = 4,713.26 + 139.5366Educ + 3.3488Exper
D) To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses) , Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel partial outputs corresponding to these models are available and shown below. Model A: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Train + β<sub>4</sub>Gender + ε Model B: Salary = β<sub>0</sub> + β<sub>1</sub>Educ + β<sub>2</sub>Exper + β<sub>3</sub>Gender + ε Using Model B, what is the regression equation for males? A) = 4,713.26 + 139.5366Educ + 3.3488Exper + 609.25Gender B) = 5,322.51 + 139.5366Educ + 3.3488Exper C) = 4,713.26 + 139.5366Educ + 3.3488Exper D) = 4,663.31 + 140.6634Educ + 3.3566Exper = 4,663.31 + 140.6634Educ + 3.3566Exper

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