May I ask how to solve the below questions in steps? Thank you~

Suppose that you are tasked with estimating the primary determinants of annual salaries in the USA. You initially obtain data (a sample) of n observations which contains the following variables for each individual in your sample: salary; , gender; , education; and parentSalary; . Here salary; is specified in dollars per year, gender, is an indicator variable equal to 1 if female and 0 for non-female, age; is specified in years, education; is specified in years, and parentSalary; is the average of the individuals parents salaries specified in dollars per year. (a) Consider the regression specification wages, = Bo + Bigender; + e; . You use some statistical software and estimate that Bo = 55,000 and , =-11, 000. Interpret both estimated coefficients. (b) Now consider instead the regression specification In(wages;) = Bo + Bigender, + Byeducation; + e;. You use some statistical software and estimate that B2 = 0.053. Interpret the estimated value of B2. (c) Consider instead the regression specification In(wages;) = Bo + Bigender; + Byeducation; + B3 In(parentSalary;)e;. You use some statistical software and estimate that By = 0.8. Interpret the estimated value of B3. (d) Suppose you obtain more variables. Specifically, you now have n observations and j independent variables, where n = j - 1. Suppose you run an OLS regression of Y, on your j - 1 covariates and a constant. What is the RZ ? Explain why you get this result and whether you have good explanatory power of the Y, values in your sample and outside your sample