Question

This question requires using Rstudio. This is following commands to install and import data into R:

> install.packages("ISLR")
> library(ISLR)
> data(Wage)

The required data installed and imported, now this is description of the data:

This dataset contains economic and demographic data for 3000 individuals living in the mid-Atlantic region. For each of the
3000 individuals, the following 11 variables are recorded:

year: Year that wage information was recorded
age: Age of worker
maritl: A factor with levels 1. Never Married 2. Married 3. Widowed 4. Divorced and 5.
Separated indicating marital status
race: A factor with levels 1. White 2. Black 3. Asian and 4. Other indicating race
education: A factor with levels 1. < HS Grad 2. HS Grad 3. Some College 4. College Grad
and 5. Advanced Degree indicating education level
region: Region of the country (mid-atlantic only)
jobclass: A factor with levels 1. Industrial and 2. Information indicating type of job
health: A factor with levels 1. <=Good and 2. >=Very Good indicating health level of worker
health ins: A factor with levels 1. Yes and 2. No indicating whether worker has health insurance
logwage: Log of workers wage
wage: Workers raw wage

This question continues with the Wage dataset.

You wish to fit a multiple regression model to predict wage using year, age, and jobclass.

However, you are interested in whether the change in wage as a worker ages differs between

industrial workers and information workers. Fit the appropriate model and test the

hypothesis of interest. Include your results and your conclusion.

{Note: I understand the initial model would be "fit=lm(wage~year+age+jobclass,data=Wage)",
now the interpretation of given interest ("whether the change in wage as a worker ages
differs between industrial workers and information workers") implies to me that I need
to fit another model (maybe includes an interaction term?) because I do not think the
initial model is enough. If so, what would that other model would look like?
After that, I would run an anova test between two models and make a decision.
That is my thinking in this question. If it is not, please explain how it should be done.}

Please provide all necessary codes using Rstudio.

Answer 1