Alternative Resources (Tutorials)

For curious students who want to explore R beyond the course requirements:

General R & Data Science

• R for Data Science (2nd Edition): The gold standard introduction to data science with R. Covers fundamentals, visualization, and data wrangling in one cohesive resource. No prior experience needed.

  https://r4ds.hadley.nz/

• ModernDive: Teaches confidence intervals, hypothesis testing, and regression using R—ideal for statistics students. Simulation-based approach.

  https://moderndive.com/

• Hands-On Programming with R: Written for non-programmers, teaches R through probability-based projects (dice, cards, slot machines). Great bridge to statistics concepts.

  https://rstudio-education.github.io/hopr/

ggplot2 Visualization

• ggplot2: Elegant Graphics for Data Analysis: The authoritative visualization guide by ggplot2’s creator. Comprehensive coverage from basics to advanced customization.

  https://ggplot2-book.org/

• R Graphics Cookbook: 150+ recipes for creating specific graphs. Excellent reference when you know what visualization you want to create.

  https://r-graphics.org/

• A ggplot2 Tutorial for Beautiful Plotting in R: Extensive tutorial with 188+ example plots showing step-by-step customization.

  https://www.cedricscherer.com/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/

• The R Graph Gallery: Hundreds of graph examples with reproducible code, organized by chart type.

  https://r-graph-gallery.com/

Tidyverse

• Tidyverse Skills for Data Science: Comprehensive course covering the entire tidyverse ecosystem from Johns Hopkins.

  https://jhudatascience.org/tidyversecourse/

• The Tidyverse Cookbook: Recipe-based guide with code solutions for common data tasks. Great for quick reference.

  https://rstudio-education.github.io/tidyverse-cookbook/

Video Content

• MarinStatsLectures: 250+ videos pairing statistical concepts with R implementation. Covers descriptive stats through regression.

  https://www.statslectures.com/r-stats-videos-tutorials

• Plotting Anything with ggplot2: 4.5-hour workshop by the ggplot2 maintainer. Originally a paid conference workshop, now free.

  https://youtu.be/h29g21z0a68

• David Robinson’s TidyTuesday Screencasts: 80+ unscripted screencasts showing real-world data analysis with tidyverse. Searchable by function.

  https://www.rscreencasts.com/

Quick Reference

• Posit Cheatsheets: Essential 1-2 page PDFs for dplyr, ggplot2, tidyr, and more. Keep these bookmarked.

  https://posit.co/resources/cheatsheets/

Base R

• CRAN “An Introduction to R”: The official manual. Canonical coverage of types, subsetting, vectorization, base graphics, and the modeling API.

  https://cran.r-project.org/doc/manuals/r-release/R-intro.html

• Deep R Programming: Rigorous coverage of R semantics, performance, and numerical computing. Ideal after you’re comfortable with basics.

  https://deepr.gagolewski.com/