Learn how to
- explore, groom, visualize, and analyze data
- make all of that reproducible, reusable, and shareable
- using R
Selected topics
- Introduction to R and the RStudio IDE; scripts, the workspace, RStudio Projects
- Generate reports from R scripts and R Markdown
- Care and feeding of data in R
- Data manipulation and split-apply-combine with dplyr and tidyr
- Data visualization with ggplot2
- Graphs and descriptive stats for quantitative and categorical variables
- Writing R functions
- Coding style and project organization
- Version control with Git; collaboration via GitHub
- Character data; regular expressions
- Interactive pages, apps, and graphics with Shiny
- Get data off the web and expose data, code, results on the web
- Distribute data and code via an R package
- Automate an analytical pipeline, e.g. via Make
More info?
Use the navigation bar above!
@STAT545 on Twitter
The course organization on GitHub: https://github.com/STAT545-UBC
Repo that creates this website: https://github.com/STAT545-UBC/STAT545-UBC.github.io