https://dacss.github.io/DACSS_601_Summer2023_Sec1/posts/AudreyBertin_Homework3.html

[giscus[bot]]

https://dacss.github.io/DACSS_601_Summer2023_Sec1/posts/AudreyBertin_Homework3.html

How did the 2022 F1 Rule Change Affect the Sport?

https://dacss.github.io/DACSS_601_Summer2023_Sec1/posts/AudreyBertin_Homework3.html

[sp-conway]

Audrey,

Really nice job here. I included some notes I took as I read.

Audrey Notes

• Is it easier to pass?
  • Relabel post_rules_change and title legend appropriately. Make sure the levels are descriptive rather than simply TRUE/FALSE. For example, try labeling them “Pre rules change” and “post rules change”. Or actually, consider just adding a vertical line to the plot (maybe with a text box too?) to demarcate when the rules change happened.
  • I find the “avg positions gained…” plot to be a bit confusing. I would relabel the levels.
  • With so few years, I might actually labeling every year on the y axis.
  • I think considering above/below expectation is a worthwhile step to take.
• How have lap times changed?
  • Again, relabel labels.
  • Good plot, though I might like to see the actual raw data rather than an estimated density curve.
  • I like the plot showing difference in average lap time pre/post rules change.
    • Make sure you specify the order you subtracted things in. Something like Post - Pre, because I had a hard time interpreting it at first. The fill of the bars helps, but I would be as explicit as possible.
    • Classification by track type is a good idea.
• Reliability
  • Make sure to emphasize you are referring to reliability of the actual cars. In social science, this term often refers to reliability of our estimates, or something similar.
  • What does retire mean in a race? Make sure to define it for the reader. I assume it means that the car didn’t finish, but I would say so explicitly prior to the graph.
  • Relabel mechanical failure legend labels
  • I like the idea for the retirement causes graph…but I might try the following
    • Cause on the x axis, # of retirements on the y axis, bar for each cause (dodge), filled by color
    • The geom_segment() is a bit confusing
• Regulation change shakeup championship
  • No strong comments here! I like the colors fine. I didn’t have trouble reading it.
  • I like looking at every possible measure of success, so average finish position is good to include.
  • Great point about 11th-20th place!
• Drivers Adapting to regulations
  • Change first bar graph to dodge, not stacked
  • I would include the graph with and without car related failures.