Answer the question by providing ALL the R-codes that have been used to reach conclusions. Also include the model and the estimated model when answering. I'm not looking for an explanation but for the R-codes and summary outputs.

The wage_data we have worked with this semester is from 1985. Say you have entered a time machine and are now working for a company in 1985. Say the wage_data set is the wages of employees from competitors of your company. You have been given the job of creating a model for wages in your company. The company's policy is to provide equal pay regardless of race, gender, marital status or union membership. Use the wage data used to create model for competitive wages for the company. Code to read in data set below.

wage_data <- read.csv("https://sites.google.com/site/bsherwood/wage_data.csv")

1. Explain the model you have fit and the steps you have taken to get this final model.
2. What would the model estimate the hourly wages for someone with the following characteristics: (occupation: Sales, sector: Manufacturing, union: no, education: 16, experience: 10, age: 45, gender: male, marital status: yes, race: Hispanic, south: yes).
3. Say you have an exceptional employee, for instance one you would rank at the .975 percentile. Would you recommend using the model's wage for this employee? Why or why not?