Discipline-Based Education Research Group


Date of this Version


Document Type



DBER Group Discussion on 2016-10-20


Copyright (c) 2016 Jordan Harshman


When carrying out quantitative discipline based educational research projects, researchers have a variety of choices when it comes to which statistical package s/he chooses to use. In this presentation, I will convey how one programming language, R, has not only provided an abundance of advantages, but has transformed the way I see data analysis. R is a free program with thousands of add-in packages capable of doing a majority of basic and advanced statistical techniques and graphics. By investigating a hypothetical data set through cluster analysis, I will present how 1) defining custom functions efficiently allows for iterative exploratory investigations, 2) programmatic loops can perform millions of analyses in seconds, 3) relatively simple interactive programming greatly enhances documentation and reproducibility, and 4) (time permitting) programming in R allows for a new perspective on data visualization. If you plan to attend, please complete this very brief survey (if you haven't already) so I can tailor the presentation in a way that will be more meaningful to you: https://goo.gl/forms/Gao8vc1bNdfIEkit1.