This is a template repository for problem sets for the Spring 2024 edition of BST 258. As the course progresses, some of our focus will transition to applying techniques and tools from statistical causal inference in examples of data analysis. Doing so in the real world requires proficiency with the tools necessary to ensure computationally reproducible results are obtained from code produced to implement a given analysis. At a bare minimum, such tools include
- Version control, e.g., with
gitand collaborative programming platforms like GitHub. If you are new to version control, you may find the introductory workshop developed and maintained by Software/Data Carpentry useful. - Virtual environments, which help to ensure that the software dependencies
of a given project remain consistent across potentially different computing
environments (including, e.g., your own machine later in time). We will use
the
renvpackage for the R programming language and environment. - Literate programming notebooks, which help to embed code and results in a
single plain-text document, ideally in a manner that can be both easily read
and converted into a variety of formats. We will use
Quarto, an open-source scientific and technical publishing system that extendsR Markdown.
Note the directory structure of this repository
$ tree -L 2
.
├── README.md
├── refs.bib
├── renv
│ ├── activate.R
│ ├── library
│ └── settings.json
├── renv.lock
└── template.qmd
3 directories, 6 files
which includes an renv directory (and associated .Rprofile); a Quarto
file template.qmd with corresponding BibTeX database refs.bib; and a few
hidden files (like .here from the here R package
and .gitignore) and directories (like .git). It is important that you
familiarize yourself with these tools, including their basic anatomy.