Exhibit 17.7.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,
Gender = the gender of an individual;1 for males,and 0 for females.
The regression results for the models,
Model A: Salary = β₀ + β₁Educ + β₂Exper + β₃Gender + β₄Exper × Gender + ε,
Model B: Salary = β₀ + β₁Educ + β₂Exper + ε,are summarized below. Note.The values of relevant test statistics are shown in parentheses below the estimated coefficients.
Refer to Exhibit 17.7.What is the value of the test statistic for testing the joint significance of Exper and Exper × Gender in Model A?

Question

Exhibit 17.7.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,
Gender = the gender of an individual;1 for males,and 0 for females.
The regression results for the models,
Model A: Salary = β₀ + β₁Educ + β₂Exper + β₃Gender + β₄Exper × Gender + ε,
Model B: Salary = β₀ + β₁Educ + β₂Exper + ε,are summarized below.

Note.The values of relevant test statistics are shown in parentheses below the estimated coefficients.
Refer to Exhibit 17.7.What is the value of the test statistic for testing the joint significance of Exper and Exper × Gender in Model A?

Quizplus · Accepted Answer

The Answer of Exhibit 17.7.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, Gender = the gender of an individual;1 for males,and 0 for females. The regression results for the models, Model A: Salary = β₀ + β₁Educ + β₂Exper + β₃Gender + β₄Exper × Gender + ε, Model B: Salary = β₀ + β₁Educ + β₂Exper + ε,are summarized below. Note.The values of relevant test statistics are shown in parentheses below the estimated coefficients. Refer to Exhibit 17.7.What is the value of the test statistic for testing the joint significance of Exper and Exper × Gender in Model A?