This page contains links to journal articles, blog posts, webpages, etc., that we (the instructors) believe may be useful to you, or at the very least interesting. Bold articles are ones that we consider must-reads but don’t have enough time to actually assign. And to be clear, must-read means that people will probably assume you’ve read this and know the basic points.
Peters (2004) “The Zen of Python.” – A list of 19 principles for writing better Python code; the principles also apply to writing better R code.
Hill (2019) “Meet xaringan.” – There are a ton of resource for learning how to make slides using R. Too many to list here. I like this one because it’s accessible, funny, visually appealing, and will help you make slides that you’re proud of. (By the way, UO has theme you can use.)
Bryan (2019) “Happy Git with R.” – Interested in using GitHub for version control? Jenny Bryan will guide you through the process and metaphorically hand you a tissue when you’re screaming with frustration.
Patil (2020) “ggstatsplot” – A very useful R package for creating visuals to display some basic univariate and bivariate descriptives.
YouTube series on linear algebra
PSY 611 – Don’t forget everything we covered last term!
Dunn & Smyth (2019) Generalized Linear Models With Examples in R – if you’re looking for a supplemental (free, online) textbook to cover general and generalized linear models, I highly recommend this one. It includes useful tidbits, like coding factors, an expansion on the matrix algebra notation for multiple regression, and an extended section on the R code useful for linear models. Plus, it expands to cases we don’t cover in class.
Silver (May 2016) How I Acted Like A Pundit And Screwed Up On Donald Trump – Nate Silver discusses how he allowed bias into his polling models and missed a prediction he could have made.
Silver (Nov 2016) Why FiveThirtyEight Gave Trump A Better Chance Than Almost Anyone Else – Nate Silver discusses how his models are bias and theory-free and 538 got it right.