[Use R/ R Studio] A researcher wonders whether males get paid more, on average, than females at a large firm. She interviews 50 employees and collects data on each employee's hourly wage (Wage in $), years of higher education (EDUC), years of experience (EXPER), age (Age), and a Male dummy variable that equals 1 if male, 0 otherwise. Data can be found in https://docs.google.com/spreadsheets/d/1OuwjChPQ41zyKZLhaf-NW3ObxrXckMy0qTcZChe4Los/edit?usp=sharing

1) Use R estimate: Wage =₀+₁EDUC +₂EXPER +₃Age +₄Male +. Based on the result, what is your opinion about the fitness/usefulness of the model. And explain.

3) Which variables in your model significantly in explaining Wage(employee's hourly wage) at the 5% level? Interpret the estimated coefficient (slope) for variables significantly explaining Wage.

4) What are the assumptions for the linear regression analysis.

5) Please check the model assumptions and provide all the plots for assumptions check. And discuss if any of the assumptions violated?

6) If violated, which assumption is being violated? which part of your result became unreliable? What remedy measure could you do?Apply what you proposed and insert the R output below.

8) Based on the revised results, which variables in your model significantly in explaining Wage (employee's hourly wage) at the 5% level?