A curated list of learnR and {swirl} related resources. LearnR and {swirl} are R-Packages for learning R in R, but not only limited to the R Language.
In the first part you find links to source code, documentation & community of the packages itself. In the second part we list courses made with learnR or {swirl}. A third part list further resources for learning R.
You're welcome to add new stuff or report glitches. See contributing.md how to pull requests.
- github-page - Official Homepage of the Package.
- github-repo - Official github repository.
- CRAN - CRAN canonical URL.
- rdocumentation.org - Package Documentation.
- libraries.io - Page on Libraries.io.
- rdrr.io - Page on rdrr.io.
- swirlstats.com - Official Homepage of the Package.
- github-repo for package - Official github repository for the package.
- github-repo for swirlify - Toolbox for writing swirl courses.
- github-repo for courses - Official github repository for the courses, see also Made with Swirl.
- rdocumentation.org - Package Documentation.
- CRAN - CRAN canonical URL.
- libraries.io - Page on Libraries.io.
- rdrr.io - Page on rdrr.io.
- twitter - Twitter Account.
- google.group - Discussion Group.
- Setting Up R - Set up your computer to use R, JJ Allaire.
- Data Basics - Learn how to look at data with R, JJ Allaire.
- Filtering Observations - Learn how to filter your data, JJ Allaire.
- Sumarizing Data - Learn how to summarise a table of data, JJ Allaire.
- Creating New Variables - Learn how to derive new variables from a data frame, JJ Allaire.
- vegawidget Overview - Learn vegawidgets, Ian Lyttle.
- Data Literacy - Understanding Visualizations, Ted Laderas.
- OHSU Tutorial Tutorial for OHSU Data Science Institute, see also github - Ted Laderas and Jessica Minnier.
- Tidyeval - by Ian Lyttle.
- learningAnalytics - Tutorials covering various statistical techniques by Brad Boehmke.
- “Hello”: An introduction to learningAnalytics
- “EDA”: Exploratory Data Analysis
- “Unsupervised”: Principal Components Analysis & Cluster Analysis
- “Linear Regression”: Linear Regression
- “Supervised Classification”: Logistic Regression & Discriminant Analysis
- “Resampling”: Leave-One-Out Cross-Validation, k-Fold Cross Validation, & Bootstrapping
- “Model Selection”: Best Subset & Stepwise Selection for Linear Models
- trainR - Interactive R Tutorials by Aravind Hebbali.
- data-wrangling-with-dplyr-part-1
- data-wrangling-with-dplyr-part-2
- data-wrangling-with-dplyr-part-3
- hacking-strings-with-stringr
- import-data-in-r-part-1
- import-data-in-r-part-2
- introduction-to-tibbles
- readable-code-with-pipes
- work-with-date-and-time-in-R
- working-with-categorical-data
- rexercises - R-Exercises by Lan Huong Nguyen.
- data_to_R
- vectors_and_matrices
- lists_and_data_frames
- programming
- plotting
- RKurs - German R Exercises by Daniel Lüdecke.
- YARD - Yet Another R Demo by Paul Egeler.
- adventr - An Adventure in Statistics by Andy Field, see also Book-Page.
- Why you need science
- Reporting research, variables and measurement
- Summarizing Data
- Fitting models (central tendency)
- Presenting data
- z-scores
- Probability
- Inferential statistics
- Robust estimation
- Hypothesis testing
- Modern approaches to theory testing
- Assumptions
- Relationships
- The general linear model
- comparing two means
- Comparing several means
- Factorial designs
- Advanced R - Advanced R Programming by Roger Peng
- ConoceR - (es) ConoceR by David Duncan
- DataScience - Data Science and R by Wush Wu
- EDA - Exploratory Data Analysis by Team swirl
- GetCleanData - Getting and Cleaning Data by Team swirl
- Google Forms - Google Forms Course by Sean Kross
- Estadistica - (es) Programacion Estadistica R by Ismael Fernández
- Programando en R - (es) Programando en R by José R Sosa
- Psychology Statistics - Psychology Statistics by Kevin R. Carriere
- QSS - qss-swirl by Kosuke Imai
- R Programming - R Programming by Team swirl
- R Programmieren - (de) R Programmieren by Stephan Weibelzahl
- R Environment - The R Programming Environment by Roger Peng
- RegEx - Regular Expressions by Jon Calder
- RegModel - Regression Models by Team swirl
- Inference - Statistical Inference by Team swirl
- Short Introduction - A (Very) Short Introduction to R by Claudia Brauer
Some Stuff at the end to check a new editor called gitpod.io. Ok, wait.