Assessing flight trends

Wow! You've already extracted quite a bit of information from your flights_xts data. Visualizing time series data - and various values derived from these data - is a critical component of any time series analysis, whether you are interested in stock returns, user retention, or opinion polls.

On the right you can see a slightly cleaned version of the plot you generated in the previous exercise. Which of the following is a reasonable conclusion to draw from this plot?

Before drawing any conclusions, be sure to familiarize yourself with the different axis scales produced by plot.zoo(). For example, diverted flights are generally on a much smaller scale (0 - 0.4%) than delayed flights (0 - 30%).

Possible answers

The largest number of flight delays occurred in the first half of 2011.

There is an overall upward trend in the number of flights arriving in Boston over time.

A relatively large percentage of flights are cancelled in December and January of most years.

Late 2013 and early 2014 saw a greater percentage of diverted flights than cancelled flights.

Exercise

Assessing flight trends

Instructions

Possible answers