Around this time last year, I uploaded two of my term papers to this blog, as I believed they might be of interest to my readers. Today, as a bit of a Christmas present, I’m back to do it again!
Linked below is a project I completed this semester for one of my statistics courses; the requirements of the assignment were to:
- independently gather and organize data, readying it for statistical analysis
- build, test, and compare different multiple linear regression models
This paper specifically focuses on determining which factors best predicted state-level turnout during the 2016 presidential election, with some fun variables and some serious variables. Since it was for a stats class, the word count falls on the shorter side — in fact, I’ve published longer pieces to this site. Overall, though, the findings weren’t too shocking or noteworthy, but that’s just how it goes sometimes. ¯\_(ツ)_/¯
I do most of my statistical work in R, so the code (and relevant output) is at the very bottom of the document, if you want to poke around for yourself. The dataset is also available for download on my GitHub.
Check it out:
