無料で読めるR教材

少しずつ埋めていきます

全般

• SONG Jaehyun・矢内勇生.『私たちのR: ベストプラクティスの探求』
• 森知晴.『卒業論文のためのR入門』
• Nathaniel D. Phillips. YaRrr! The Pirate’s Guide to R
• Chester Ismay and Albert Y. Kim. Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
• Hadley Wickham and Garrett Grolemund. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data [Korean]
• Hadley Wickham. Advanced R (2nd Ed.)
• Hadley Wickham and Jennifer Bryan. R Packages: Organize, Test, Document and Share Your Code
• Colin Gillespie and Robin Lovelace. Efficient R programming: A Practical Guide to Smarter Programming
• Roger D. Peng. R Programming for Data Science
• Garrett Grolemund. Hands-On Programming with R: Write Your Own Functions and Simulations
• The Carpentries. R for Reproducible Scientific Analysis
• Monash Data Fluency . Reproducible Research in R
• Garrett Grolemund. Master the Tidyverse
• Hadley Wickham. The tidyverse style guide
• Oscar Baruffa. Big Book of R
• Mark van der Laan, Jeremy Coyle, Ivana Malenica, Rachael Phillips, and Rachael Phillips. Targeted Learning in R: Causal Data Science with the tlverse Software
• Andrew Ba Tran. R for Journalists
• nissinbo. 「医療情報DB解析のためのデータハンドリング大全」
• 김길환. 2021. R 프로그래밍 (개정판)
• Yang Feng and Jianan Zhu. R Programming: Zero to Pro
• Socio-Econ. 『資料 R&Rパッケージを利用した社会経済データの取得と利用方法(作成中)』
• 山本雅資『2021年度データ分析入門』](https://yamamoto-masashi.github.io/DSlec/)
• Jaeyeon Kim. Computational Thinking for Social Scientists.
• Syunsuke Fukuda.『Rビギナーズガイド』
• R Bootcamp
• Data Science Course in a Box
• Roger D. Peng, Sean Kross, and Brooke Anderson. Mastering Software Development in R

可視化

• Kieran Healy. Data Visualization: A practical introduction
• Claus O. Wilke. Fundamentals of Data Visualization
• Winston Chang. R Graphics Cookbook (2nd Ed.)
• The R Graph Gallery
• World Bank. R Econ Visual Library

R Markdown

• Yihui Xie, J. J. Allaire, and Garrett Grolemund. R Markdown: The Definitive Guide
• Yihui Xie, Christophe Dervieux, and Emily Riederer. R Markdown Cookbook
  • 『R Markdown クックブック』
• Yihui Xie, Amber Thomas, and Alison Presmanes Hill. blogdown: Creating Websites with R Markdown
• Yihui Xie. bookdown: Authoring Books and Technical Documents with R Markdown
• Resul Umit. Writing Reproducible Research Papers with R Markdown
• Matthew Crump. Open tools for writing open interactive textbooks
• 高橋康介.「[連載] R Markdownで楽々レポートづくり」

Shiny

• Hadley Wickham. Mastering Shiny.
• David Granjon. Outstanding User Interfaces with Shiny.

計量経済学、計量政治学、統計学

• 土井翔平.『Rで計量政治学入門』
• 津田裕之.『Rによる統計入門』
• 安藤道人・三田匡能.『Rで学ぶ計量経済学と機械学習』
• Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer. Introduction to Econometrics with R
• Florian Heiss. Using R for Introductory Econometrics, 2nd edition
  • Pythonバージョン
• Neale Batra (Ed.). The Epidemiologist R Handbook
• Adam Fleischhacker. A Business Analyst’s Introduction to Business Analytics

ベイジアン統計学

• A Solomon Kurz. Statistical Rethinking with brms, ggplot2, and the tidyverse.
• Alicia A. Johnson, Miles Ott and Mine Dogucu. Bayes Rules! An Introduction to Bayesian Modeling with R.
• Virgilio Gómez-Rubio. Bayesian inference with INLA.

因果推論

• 矢内勇生.『KUT 計量経済学応用: 統計的因果推論入門』
• Paul C. Bauer. Applied Causal Analysis (with R)
• Gertler, Paul J., Sebastian Martinez, Patrick Premand, Laura B. Rawlings, and Christel M. J. Vermeersch. Impact Evaluation in Practice, Second Edition
  • [Solution] Liam F. Beiser-McGrath. Impact Evaluation in Practice: Solutions for Second Edition in R

その他

• 国里愛彦・竹林由武.『今日からできる再現可能な論文執筆』
• Max Kuhn and Julia Silge. Tidy Modeling with R
• Paul Roback and Julie Legler. Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R
• Rafael A. Irizarry. Introduction to Data Science: Data Analysis and Prediction Algorithms with R
• Julia Silge and David Robinson. Text Mining with R: A Tidy Approach
• Pablo Casas. Data Science Live Book
• Mathias Harrer, Pim Cuijpers, Toshi A. Furukawa, and David D. Ebert. Doing Meta-Analysis in R: A Hands-on Guide
• 슬기로운 통계생활. 딥러닝 공략집 with R
• Chris Brown, Murray Cadzow, Paula A Martinez, Rhydwyn McGuire, David Neuzerling, David Wilkinson, Saras Windecker. Github actions with R.
• Yan Lu and Sharon L. Lohr. R Companion for Sampling: Design and Analysis (3rd Ed.)