R for Public Health
The course examines principles & methods underlying the use of R, emphasizing multi-disciplinary, collaborative, & real world uses. We will emphasize practices for collaborative coding using Git/GitHub repositories for storing & sharing code to benefit not only your current collaborators but your most frequent collaborator. We will introduce best practices for organizing data & projects, how to create reproducible examples (a.k.a reprex) for when you get stuck and need to ask the R community for help (but can’t share a full dataset because it’s too large or contains confidential information). Application of principles will be taught through scenarios that public health practitioners encounter.
Topics
- Apply knowledge of R to support ongoing analytic work in epidemiology and biostatistics; Effectively engage with public health practitioners in the use of R to address current public health and/or policy issues; Identify best practices for project management, programming, and version control when contributing data to evaluate and/or support effective public health interventions; Select appropriate methods for importing, cleaning, and analyzing data within R; Develop strategies for addressing issues that arise when combining data from multiple, complex data sources; Create meaningful visualizations of data and have a basic understanding of tools available through R to present data (including R markdown, R Shiny) Leverage existing open-source resources for continued learning and problem solving.
Official catalogue course objectives and student learning outcomes
Sources
- Course catalogue ↗2026-2027