Stats 50: Mathematics of Sports
Spring 2019

• Home
• Description
• Staff
• Schedule
• R
• Grade
• Homework
• Project
• Piazza
• References
• Advice
• Previous Projects

R

For every statistical technique learned in this class, we will also learn how to implement in on real data in R, the free statistical language. Friday is R day, meaning that students are expected to bring laptops to class on Friday and follow along by running the same code in R sessions on their own laptops. Visit r-project.org to download R for free before the first R day (Friday, April 5).

Resources

If you are struggling to learn R, check out this blog post. It links to a lot of valuable resources for learning R. Perhaps the most pain-free way to learn the basics of R is to go through an in-browser course. Three such courses are:

• Try R (Code School). No sign-up necessary! Just click and get started.
• Introduction to R (DataCamp). Requires you to set up a FREE account.
• swirl (DataCamp). Requires you to set up a FREE account.

For quicker help, check out this R reference card.

In-class material

Each week, we will upload the dataset, questions and solutions on which we will focus during Friday's R session.

Tutorial 7 (Friday, May 17)

• Chicago Sky 2018 schedule (Website to scrape)
• 7-rvest-blank.R (R script ot modify)
• 7-rvest-complete.R

Tutorial 6 (Friday, May 10)

• 6-rasch-blank.R (R script to modify)
• NBApbp11-12.csv
• 6-rasch-complete.R

Tutorial 5 (Friday, May 3)

• 5-bradley-terry-blank.R (R script to modify)
• NCAAfootballl2018.csv (from prwolfe.bol.ucla.edu)
• FBSteams.txt (list of teams in Football Bowl Subdivision)
• 5-bradley-terry-complete.R (R script to modify)

Tutorial 4 (Friday, April 26)

• 4-regression-to-the-mean-blank.R (R script to modify)
• NBAtotals16-16.csv
• 4-regression-to-the-mean-complete.R (R script to modify)

Tutorial 3 (Friday, April 19)

• 3-wOBA-blank.R (R script to modify)
• MLBpbp2018.csv (from retrosheet.org)
• 3-wOBA-filled.R (Solutions - filled in as in class)

Tutorial 2 (Friday, April 12)

• 2-basketball.R (an R script that you can modify)
• 2-basketball.pdf (pdf file containing the problem descriptions and exercises)
• 2-basketball-solutions.pdf (same as above, but with solutions)
• 2-basketball-stats216.pdf (Stats 216 lecture containing some additional exercises)

Tutorial 1 (Friday, April 5)

• 1-data-viz-and-manipulation.r (R script to modify)
• 1-data-viz-and-manipulation_solution.r (Solutions)
• receiving2018.csv (from Pro-Football-Reference.com)
• receiving2015.csv (from Pro-Football-Reference.com)