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Exhibit 17

Question 41

Multiple Choice

Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and 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.
Also,the following Excel partial outputs corresponding to the following models are available:
Model A: Salary = β0 + β1Educ + β2Exper + β3Train + β4Gender + ε Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and 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. Also,the following Excel partial outputs corresponding to the following models are available: 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 Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for females? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) Model B: Salary = β0 + β1Educ + β2Exper + β3Gender + ε Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and 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. Also,the following Excel partial outputs corresponding to the following models are available: 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 Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for females? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for females?


A) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and 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. Also,the following Excel partial outputs corresponding to the following models are available: 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 Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for females? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender
B) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and 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. Also,the following Excel partial outputs corresponding to the following models are available: 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 Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for females? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) = 5322.5011 + 139.5366Educ + 3.3488Expe
C) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and 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. Also,the following Excel partial outputs corresponding to the following models are available: 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 Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for females? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D) = 4713.2506 + 139.5366Educ + 3.3488Expe
D) Exhibit 17.2.To examine the differences between salaries of male and female middle managers of a large bank,90 individuals were randomly selected and 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. Also,the following Excel partial outputs corresponding to the following models are available: 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 Refer to Exhibit 17.2.Using Model B,what is the regression equation found by Excel for females? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D)

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