PART 1: Use the following regression output to answer the questions MODEL 1 sala
ID: 3181477 • Letter: P
Question
PART 1: Use the following regression output to answer the questions MODEL 1 salary 71.138 22.184(assistant 22.385 (associate) 4.605(male) 1.524(exper) .0762 (exper 3.556 (male assistant) (2.937) (0.007) (0.978) (se) (4.931) (4.764) (3.479) (0.392) Adj R2 476 In this model we are estimating the effect of included variables on annual salary of college professors Dataset includes 600 college professors n 600 salary annual salary in thousands of US dollars assistant lif assistant professor, 0 if not associate 1 if associate professor, 0 if not male 1 if male, 0 if not exper of years experience OMITTED BASELINE IS FULL PROFESSORExplanation / Answer
The term male*assistant tells us that how much effect a male assistant would bring to the salary.
All other factors remaining constant, salary would decrease by 4.605 if the person is a male.
Salary=71.138-22.184(assistant)-22.385(associate)-4.605(male)+1.524(exper)-0.0762(exper^2)+3.556(male*assistant)
Male and Assistant Prof:-71.138-22.184(1)-22.385(0)-4.605(1)+1.524(5)-0.0762(5^2)+3.556(1*1)=71.138-22.184-0-4.605+7.62-1.905+3.556=53.62
Female and Assistant Prof:-71.138-22.184(1)-22.385(0)-4.605(0)+1.524(5)-0.0762(5^2)+3.556(0)=54.669
Male and Associate Prof:-71.138-22.184(0)-22.385(1)-4.605(1)+1.524(5)-0.0762(25)+3.556(1*0)=49.863
Female and Associate Prof:-71.138-22.184(0)-22.385(1)-4.605(0)+1.524(5)-0.0762(25)+3.556(0*0)=54.468
Difference (Assistant Prof)=53.62-54.669=-1.049
Difference (Associate Prof)=49.863-54.468=-4.605
No data given for FULL PROFESSOR
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.