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To Examine the Differences Between Salaries of Male and Female

Question 59

Multiple Choice

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 + β1 Educ + β2 Exper + β3 Train + β4 Gender + 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   When testing the individual significance of Train in Model A,what is the test conclusion at 10% significance level? A)  Do not reject H<sub>0</sub>;Train is significant. B)  Reject H<sub>0</sub>;Train is significant. C)  Reject H<sub>0</sub>;Train does not seem to be significant. D)  Do not reject H<sub>0</sub>;Train does not seem to be significant. Model B: Salary = β0 + β1 Educ + β2 Exper + β3 Gender + 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   When testing the individual significance of Train in Model A,what is the test conclusion at 10% significance level? A)  Do not reject H<sub>0</sub>;Train is significant. B)  Reject H<sub>0</sub>;Train is significant. C)  Reject H<sub>0</sub>;Train does not seem to be significant. D)  Do not reject H<sub>0</sub>;Train does not seem to be significant. When testing the individual significance of Train in Model A,what is the test conclusion at 10% significance level?


A) Do not reject H0;Train is significant.
B) Reject H0;Train is significant.
C) Reject H0;Train does not seem to be significant.
D) Do not reject H0;Train does not seem to be significant.

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