16  Age of Planes

You are excited for your new job in the Strategy Department at Boeing, a commercial airliner manufacturer in the United States. In an effort to better understand their customer’s operations, Boeing is curious about how the age of an airplane affects its use.  

In a previous task we used the flights tibble from the nycflights13 package to answer questions about flight delays. That same package contains four other tibbles that are related to flights and can help us answer more complex questions. Run data(package = "nycflights13") to see a list of the tibbles with a brief description.

For this task your boss wants answers to two these questions:

What is the relationship between departure delays and age of the plane? What is the relationship between airline carrier and age of the plane? What else did you learn as investigated the relationship between age of plane and other variables?

  1. Join the flights and planes tibbles.
  2. For each flight, calculate the age of the plane that was used.
  3. Create a chart that looks at the distribution of departure delays by age (or age group). Do you notice any patterns?
    1. Create a new column that groups age into 0-10, 11-20, 21-30, and >30
  4. Continue to work with your age data, but join on the airlines tibble so you have the full name of the carrier.
  5. Create a chart that looks at the distribution of age by carrier. Write about patterns you see (or lack thereof).
  6. Create a third chart using any variable(s) you think will be related to age. (You can use any/all of the other tibbles in the nycflights13 package.) Write about patterns you see (or lack thereof).
  7. Render the .qmd file. Push all the files created in the rendering process into your GitHub repository.

Submit

In I-learn submit a link to the .md file containing your chart(s) on GitHub.