Thread: Regression models

Just a little confused what's being asked.. So...
I have these variables to play with:

Y: Wage is the annual Wage of an employee (response variable)
X1: Starting Wage (StWage) is the employee’s Starting Wage
X2: Years of Experience (YrsExp) is the number of years the employee has been in the workforce
X3: Previous Experience (PrevExp) an employee’s Years of Previous Experience.
X4: Years of Education (YrsEd) is the total number of years of education.
G: Gender is coded M if employee is male, F if the employee is female.
D: Education Level is one of five categories, 1: Post Graduate, 2: Bachelor’s Degree, 3: TAFE,
4: Completed High School, 5: High School dropout.

I am asked 2 questions (of which confuse me a little)

1)Estimate equation Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ + ε with the addition of M as an explanatory variable (i.e., use Females as the base). Write out the equation, with its standard errors. Now estimate the same equation, with F as an explanatory variable (i.e., use Males as the base). Write out this equation and its standard errors also. Compare these two estimations.

Here, I just filtered for either 'only' male or 'only' female data.. Then the regression. model - blah blah

2)Now estimate without the Gender variable, but with the Education dummy variables (dropping D5). Also estimate this equation, but this time dropping Education level 4 (D4) instead of level 5. Write out both equations with their standard errors. Compare these two estimations.

Now, I just used filtered 'all' data except for D5, then 'all' except D4... Then the regression model - blah blah.


Is that wrong, for 2 it seems to make extra no sense to me.

Thank you !