InfoGuides: Software: Learn R: Tutorials

R 4 DS

R for Data Science by Hadley Wickham; Mine Çetinkaya-Rundel; Garrett Grolemund Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverseâ??a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly. You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way. You'll understand how to: Visualize: Create plots for data exploration and communication of results Transform: Discover variable types and the tools to work with them Import: Get data into R and in a form convenient for analysis Program: Learn R tools for solving data problems with greater clarity and ease Communicate: Integrate prose, code, and results with Quarto
Call Number: Available Online through the author
ISBN: 9781492097402
Publication Date: 2023-07-18

This book is one of the best resources and good to either read or refer to. However, non-programmers may find it doesn't start at the beginning. For Solutions to Exercises, click here.

Comprehensive Resources

R with RStudio: Getting Started (~1.5 hrs): Shows all the basics of starting and organizing a process, opening a data file and doing basic data management and visualization. Markdown document with the code
An Introduction to R by University of Aberdeen - Focused on Ecology and Biostatistics
- To go with their Introduction to R training course
R Basics from The Epidemiologist R Handbook: Describes all the fundamentals and much more.
R: An Introduction Playlist / one video (~2.2 hrs) from Barton Paulson / datalab.cc - Goes slowly for beginners, and talks about his favorite packages such as rio, pacman, and tidyverse. Covers visualization, data management, and regression. See also his Linked-In Learning Course: R for Data Science: Analysis and Visualization

For people who know other programming langauges

Learn R in 39 minutes (39 min, Equitable Equations) - Good overview of getting started and key functions in R, but goes quickly and may use terminology some are unfamiliar with.

General Tutorials

General R Tutorials

Stat 545 - Course material on Data wrangling, exploration, and analysis with R [UBC]
- Emphasizes workflow issues, including RMarkdown and Git.
- Starts with Data but also covers function writing, make, APIs and Shiny apps.
swirl - Learn R and statistics using R itself. Only a few courses, some old/wordy.
RYouWithMe - Starts at the basics and goes at a slow and steady pace (R-Ladies Sydney)
- The site has videos and text, or you can see the YouTube Channel
DataCamp - Interactive tutorials, some free like Introduction to R and the YouTube channel
- Instructors can give free access to all tutorials for their students in classs.

R for Social Scientists

Data Carpentry Workshop Materials
- Starts with objects (not datasets)
Data Science for Social Scientists by Richard Landers
- Materials incorporate (and assume access to) DataCamp Courses
- Includes Video (YouTube) and lectures
- Starts with programming concepts first, including the old apply functions (often overly complicated)
R Documentation (Social Science Computing Cooperative- SSCC)
- Several book-like tutorials with follow-along examples and exercises
- Separate sections using base R and the tidyverse.
- Also covers basic regression and diagnostics.
Using R for Psychology Research by The Personality Project
- Older, still uses the apply functions and no tidyverse or afex
- Focuses on the psych package: Getting Started with R and the psych package
Exploratory Data Analysis in R (Colby College)
- From an undergraduate environmental science course (ES218)
- Great overview of objects and data types (assumes understanding of functions/arguments)
- Starts with dplyr, and the group_by and summarize functions, which are somewhat overly complicated
- Covers graphics in base, lattice, and ggplot and other options.
- ANOVAs don't use the afex package

Other Online Books

ModernDive: Statistical Inference via Data Science by Chester Ismay and Albert Y. Kim
An Introduction to using Political and Social Data Analysis using R by Thomas M. Holbrook - Focuses on Statistics, uses Base R for data transformations.
YaRrr! The Pirate's Guide to R by Nathaniel D. Phillips
R Programming for Data Science by Roger D. Peng - Focused on Programming
Introduction to Programming with R by Digital Science Center at Universität Innsbruck