Solved

Exhibit 17

Question 88

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 males? 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 males? 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 males?


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 males? 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 males? 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 males? 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 males? A) = 4713.2506 + 139.5366Educ + 3.3488Exper + 609.2505Gender B) = 5322.5011 + 139.5366Educ + 3.3488Expe C) = 4713.2506 + 139.5366Educ + 3.3488Expe D)

Correct Answer:

verifed

Verified

Unlock this answer now
Get Access to more Verified Answers free of charge

Related Questions

Q25: Which of the following variables is not

Q83: Exhibit 17.5.An over-the-counter drug manufacturer wants to

Q85: Exhibit 17.8.A realtor wants to predict and

Q86: Exhibit 17.8.A realtor wants to predict and

Q87: Exhibit 17.9.A bank manager is interested in

Q89: Consider the model y = β<sub>0</sub> +

Q90: Exhibit 17.3.Consider the regression model, Humidity =

Q91: For the linear probability model y =

Q92: Exhibit 17.2.To examine the differences between salaries

Q93: In the regression equation <img src="https://d2lvgg3v3hfg70.cloudfront.net/TB2339/.jpg" alt="In