AD-Approach

Approach

For this assignment, I will use the airline delay data provided with the assignment. The data compares Alaska Airlines and AM West flights to five destinations and shows whether the flights were on time or delayed.

The original data is not in a tidy format. The destinations are stored in separate columns, and the airline names are not repeated on every row. Before doing the analysis, I will first clean up the airline names and then change the destination columns from wide format to long format. My goal is to have one column for the airline, one for the flight status, one for the destination, and one for the number of flights.

I will use R with tidyverse, mainly dplyr and tidyr, to clean and reshape the data. After the data is tidy, I will calculate the number and percentage of delayed flights for each airline. I will compare the overall delay rates and then compare the airlines separately for each destination.

The main question I want to answer is whether the airline with the better overall delay rate also performs better when the destinations are compared individually. This should help show why looking only at the overall percentage can sometimes give a different picture from looking at the individual groups.

Course Material

This approach uses the Week 5 topics on tidy data, data reshaping, and transformation with tidye and dplyr.

AI Assistance

AI tools were used for general assistance and review.