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Exhibit 17

question 80

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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?


Definitions:

Production Rates

The speed at which goods are manufactured or services are provided in a specified period.

Global Labor Market

The international marketplace where labor demand and supply interact, affecting employment and wages worldwide.

Work Force

The total number of a country's or organization's employees, including both the employed and those seeking employment.

Educated Students

Individuals who have acquired knowledge, skills, and critical thinking through formal education.

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