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To Examine the Differences Between Salaries of Male and Female

question 99

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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   For a test of individual significance about gender, what is the conclusion at 5% significance level? A)  Do not reject H<sub>0</sub>; we can conclude gender is significant. B)  Reject H<sub>0</sub>; we can conclude gender is significant. C)  Reject H<sub>0</sub>; we cannot conclude gender is significant. D)  Do not reject H<sub>0</sub>; we cannot conclude gender is significant. 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   For a test of individual significance about gender, what is the conclusion at 5% significance level? A)  Do not reject H<sub>0</sub>; we can conclude gender is significant. B)  Reject H<sub>0</sub>; we can conclude gender is significant. C)  Reject H<sub>0</sub>; we cannot conclude gender is significant. D)  Do not reject H<sub>0</sub>; we cannot conclude gender is significant. For a test of individual significance about gender, what is the conclusion at 5% significance level?


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