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To Examine the Differences Between Salaries of Male and Female

question 107

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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?

Know the importance and use of electronic transactions in business.
Understand the principles of internal control and how they protect the organization.
Ability to identify and explain documents and procedures in managing cash and cash equivalents.
Knowledge of bank reconciliation processes and their importance for businesses.

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