Introduction to R for Social Scientists
University of Washington
- R for Data Science online textbook by Garrett Grolemund and Hadley Wickham. One of many good R texts available, but importantly it is free and focuses on the
tidyverse collection of R packages which form the backbone of this course.
- Advanced R online textbook by Hadley Wickham. A great source for more in-depth and advanced R programming.
- Introduction to R Workshop, recorded Oct. 11, 2018, with companion webpage.
- Intermediate R Workshop, recorded Jan. 31, 2019, with companion webpage.
- What They Forgot to Teach You About R by Jenny Bryan and Jim Hester. Great information on best practices for managing projects and R itself.
- Teacups, Giraffes, and Statistics, an illustrated and interactive introduction to R and statistics.
Weekly lecture notes and links:
1. RStudio and R Markdown
- Slides for Lecture 1: Course logistics, R/RStudio, and R Markdown
- Lecture Video for Lecture 1, recorded April 3rd, 2019
- Homework 1: Due at 11:59PM on October 1st
- Get R
- Get RStudio
- R Markdown Installation - Also has LaTeX installation instructions
- Introduction to R Markdown
- RMarkdown documentation
- R Markdown: The Definitive Guide by Xie, Allaire, and Grolemund, a comprehensive textbook on R Markdown.
- Useful RStudio cheatsheets on R Markdown, RStudio shortcuts, etc.
- Information on the
prettydoc package for nicer looking RMarkdown themes
- Presentations in RStudio for simple presentations
- Xaringan for advanced presentations
pander documentation for making tables, etc.
- Shapes and line types in base R
- Color names (PDF) in base R
2. Visualizing Data
3. Manipulating and Summarizing Data
4. Understanding R Data Structures
5. Importing, Exporting, and Cleaning Data
6. Using Loops
7. Writing Functions
8. Working with Text Data
9. Working with Geographical Data
10. Reproducibility and Model Results
This project is maintained by clanfear and includes materials from rebeccaferrell with permission.