Spring Reading Challenge
Genres

R Programming


R Programming Books

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Hands-On Programming with R: Write Your Own Functions and Simulations
R Graphics Cookbook: Practical Recipes for Visualizing Data
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Machine Learning with R
R Programming for Data Science
Dynamic Documents With R and Knitr
Report Writing for Data Science in R
Exploratory Data Analysis with R
R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics (O'reilly Cookbooks)
Modern Time Series Analysis with R: Practical forecasting and impact estimation with tidy, reproducible workflows
Mastering Shiny
Tidy Modeling with R: A Framework for Modeling in the Tidyverse
R Packages: Organize, Test, Document, and Share Your Code
Beginners Guide For Data Analysis Using R Programming
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Quotes Tagged “R Programming”

Gary Sutton
“ Statistics Slam Dunk is a wonderful book to extend your data management and statistical skills with R, especially when you love sports! ”
― Gary Sutton, Statistics Slam Dunk
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