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 + β₃ Train + β₄Gender + ε Model B: Salary = β₀ + β₁Educ + β₂Exper + β₃Gender + ε Which of the following explanatory variables in Model A is not significant at the 5% level?

Question

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 + β₃ Train + β₄Gender + ε

Model B: Salary = β₀ + β₁Educ + β₂Exper + β₃Gender + ε

Which of the following explanatory variables in Model A is not significant at the 5% level?

Quizplus · Accepted Answer

To determine if a variable is significant at the 5% level, we look at the p-values. The variable with the highest p-value is not significant. From the Excel output, we can see that the p-value for Train is 0.311, which is greater than 0.05. Therefore, Train is not significant at the 5% level. The other variables, Educ, Exper, and Gender, have p-values less than 0.05 and are significant at the 5% level.

To Examine the Differences Between Salaries of Male and Female