This site provides a foundation in using the R programming language for data analytics. It is designed to be self-taught as preparation for other courses that build on the concepts covered. Topics include:
- Data input/output
- External packages
- Data structures (vectors, data frames, lists)
- Data wrangling
- Data visualization
- Reproducible reporting
After completing these lessons, you should be able to:
- Use RStudio to write basic R commands.
- Know the distinctions between different R operators and data types, including numeric, string, and logical data.
- Use tidyverse functions to wrangle and manipulate data in R.
- Use the ggplot2 library to create plots in R.
- Reproducibly import, export, wrangle, and visualize data.
There are no prerequisites. Students are assumed to have zero prior programming experience for this course.