Author

Published

Sunday, November 17, 2024

There are plenty of free online resources to help learn R and git. Here is a quick collection of some that I came across.

Quick overviews

Andrew Heiss has quick primer on R, RStudio and tidyverse
Some useful code-snipped recepies
R and RStudio cheat sheets

Courses

Jenny Bryan has an introductory course in R, visualization, and data analysis online
Mine Çetinkaya-Rundel has an introductory course in R, visualization, and data science online
Alison Hill has an introductory course for R and ggplot2
The psyTeachR team at the University of Glasgow School of Psychology and Neuroscience has (several courses on programming, data wrangling and analyses in R)[https://psyteachr.github.io/]
Jenny Bryan’s “Happy Git and GitHub for the useR”
Software Carpentry has a course on git

Books

There is, of course, so much more out there. You can find a curated (very long) list of R ressources here. Or another, perhaps slightly more outdated one here

Footnotes

this book is mostly about statistics but uses R for examples↩︎

Citation

BibTeX citation:

@online{pfänder2024,
  author = {Pfänder, Jan},
  title = {Learning {Ressources}},
  date = {2024-11-17},
  langid = {en}
}

For attribution, please cite this work as:

Pfänder, Jan. 2024. “Learning Ressources.” November 17, 2024.

---
title: "Learning Ressources"
date: 2024-11-17
description: "An overview of a couple of freely available online ressources to learn the basics of R and git"
#image: "downloads/PNG/grp-summarize-02@4x.png"
categories:
  - R stats
# citation: 
#   url: https://samanthacsik.github.io/posts/2024-03-31-data-viz-course/
citation: true
draft: false
---

```{r}
#| label: setup
#| include: false

library(tidyverse)
library(kableExtra)
```

There are plenty of free online resources to help learn R and git. Here is a quick collection of some that I came across.

# Quick overviews

- Andrew Heiss has [quick primer on R, RStudio and tidyverse](https://evalsp24.classes.andrewheiss.com/example/rstudio-tidyverse.html) 
- Some useful [code-snipped recepies](https://posit.cloud/learn/recipes)
- [R and RStudio cheat sheets](https://posit.co/resources/cheatsheets/)

# Courses

- Jenny Bryan has an [introductory course in R, visualization, and data analysis online](https://stat545.com/)
- Mine Çetinkaya-Rundel has an [introductory course in R, visualization, and data science online](http://www2.stat.duke.edu/courses/Fall17/sta112.01/)
- Alison Hill has an [introductory course for R and ggplot2](https://dmice.ohsu.edu/bedricks/courses/cs631/)
- The psyTeachR team at the University of Glasgow School of Psychology and Neuroscience has (several courses on programming, data wrangling and analyses in R)[https://psyteachr.github.io/]
- Jenny Bryan's ["Happy Git and GitHub for the useR"](https://happygitwithr.com/)
- Software Carpentry has [a course on git](https://swcarpentry.github.io/git-novice/index.html)

# Books

- [R for Data Science: Import, Tidy, Transform, Visualize, and Model Data 2nd Edition](https://r4ds.hadley.nz/)

- [Crump, M. J. C., Navarro, D. J., & Suzuki, J. (2019, June 5). Answering Questions with Data (Textbook): Introductory Statistics for Psychology Students.](https://www.crumplab.com/statistics/)^[this book is mostly about statistics but uses R for examples]

There is, of course, so much more out there. You can find [a curated (very long) list of R ressources here](https://github.com/iamericfletcher/awesome-r-learning-resources). Or [another, perhaps slightly more outdated one here](https://paulvanderlaken.com/2017/08/10/r-resources-cheatsheets-tutorials-books/)