Data Analysis With R

Catalog description

This course guides students to proficiency in data analysis using R, equipping them with the skills to analyze quantitative data and create reports and interactive tools that support research, policy, and practice. Through weekly in-person lab sessions, students will participate in hands-on tutorials and collaborative debugging sessions to build essential coding and analytical proficiency. Key topics include data wrangling, visualization, simulation, statistical tests, and the development of interactive applications and reproducible reports. Students will gain experience with essential R packages such as ggplot2, lme4, rmarkdown, and shiny. Learning is reinforced through an individual project that includes a final report, an interactive tool, and a public repository, along with bi-weekly checkpoints to track progress and ensure skill development. Students must be proficient with data and data analysis.