Setting up a Research Environment

Before starting on our research journey, let’s make sure all of the required software is present. This week, we will introduce different technologies that require the following software to be present.

Note: Each research project may require additional software than what is listed here.

In particular, please make sure to download and install:

• R: R is a free software environment for statistical computing and graphics. Please make sure to run the latest version R version 4.1.0 (Camp Pontanezen) released on 2021-05-18.

• RStudio: RStudio is a free and open source integrated development environment (IDE) for R. There are other options to use for writing R code such as Visual Studio Code (with R Support), R GUI, GNU Emacs (with Emacs Speaks Statistics), or even a plain text editor. We’ve opted to RStudio since it is a feature-rich program for writing R code and, perhaps more importantly, used heavily in both academia and industry. In particular, we’ll be using RStudio Desktop 1.4.1106.

• R packages: R Packages are an extension to the R language that provide additional features. We’ll be using quite a few to tackle different research problems. You can install the core set of packages by opening RStudio and typing – or copying and pasting – into the console:

  install.packages(c(
   "babynames", "devtools", "gameofthrones", "ggforce", "ggraph", "ggrepel", "ggtext", 
   "ggthemes", "glue", "knitr", "RcppArmadillo", "rmarkdown", "sf", "tidyverse" 
  ))

• Compiler Toolchain (optional): Compiler Toolchains provide the opportunity to construct R packages from source code and translate code into a low-level machine language called assembly.