• Track and Field indoor mile thingy
• NASA App
• Data is plural
  
• sootopolis
• altair_theme
• tidytuesday?
• elo ranking algo
• Tree Ranking algo (could be fun)
• Track Shoe analysis:
  1. Use a allen downey’s idea of “there’s only one test” to simulate the statistical difference
  2. Start with proving that you can simulate that a given year and that year 16th time cut off is not abnormal given the data
  3. Run the old before and after approach. Take the data before the super shoe era and data after the super shoe and see if you can simulate the first year of the super shoe era ’s 16th time in using the years prior to it
  4. Then use a window approach to simulate how significant a given year’s 16th fastest time is use the 3 years around it (or maybe 3 years before it)
     1. plot a ridgeline chart where each year is on the row facet is a year, the y axis represents the frequency/histogram and the x axis is the time in seconds for the men’s mile
     2. Hypothesis is around the intro of super shoes coming intro it becomes statistically significant

This might come in handy later: https://stackoverflow.com/questions/74445505/how-to-add-html-code-to-a-quarto-website basically you can inject html into quarto (might be good for the iframe trick)