本文约5200字，建议阅读10分钟
本文分享100个统计学和R语言学习资源网站。
简介
原文：统计学 & R学习资源
编辑：庄闪闪的R语言手册
作者：CoffeeCat[1]
转载于：Coffee学生物统计的地方[2]
注：有些链接需要科学上网/较硬的英文阅读能力才能愉快地体验知识/技术带来的快感。
1.个人主页、博客、社区、论坛
北大李东风[3]
中科大张伟平[4]
谢益辉(人称谢大大)[5]：统计之都论坛[6]创始人(与之有关的统计之都[7])
统计学资源链接大全[8]：知名 统计系、统计学会、统计组织、统计软件、统计期刊的官网（该老师的主页[9]）
斯坦福大学统计系：Trevor Hastie[10]、Jerome H. Friedman[11]、Rob Tibshirani[12]
顾凯[13]：统计分析师；R、SAS、医学统计博主
revolutionanalytics[14]：一个R社区(Revolution Analytics开发了Revolution R，后来被微软收购)
r-bloggers[15]：R博客
Statistics How To[16]：统计学与SPSS, Minitab, Excel
Statistical Modeling, Causal Inference, and Social Science[17]：哥大统计“统计建模，因果推论和社会科学”
Error Statistics Philosophy[18]：统计哲学家Deborah G. Mayo
Simply Statistics[19]：三位生物统计专家的Jeff Leek[20], Roger Peng[21], Rafa Irizarry[22]的博客
FLOWINGDATA[23]：分析、数据可视化(付费)
Statistics by Jim[24]：使统计更直观
2.电子书、课程
Library Genesis[25]：外文电子书大全。结合亚马逊[26]、Routledge[27](Chapman \& Hall/CRC Texts in Statistical Science[28]、Chapman \& Hall/CRC Biostatistics Series[29])、Springer[30](Springer Statistics[31])、Elsevier[32]、Oxford University Press[33](Probability \& Statistics[34])、Cambridge University Press[35](Statistics and probability[36])……几乎可以找到你想要的一切。
电子书From Bookdown[37]:
数据科学中的R语言[38]：非常全面的R教程
R语言忍者秘籍[39]：谢大大的R教程
现代统计图形[40]：谢大大R可视化的佳作
Statistics Handbook[41]：R语言统计分析小册子（有类似的中文的：薛毅老师的《统计建模与Ｒ软件》）
R for Data Science[42]：COPSS奖得主、RStudio首席科学家Hadley Wickham[43]的倾力之作，学习tidyverse[44]重要语法的不二之选
Advanced R[45]：Hadley Wickham[46]的提高R语言编程技能(本书的习题解答[47])
R Graphics Cookbook[48]：R基础绘图圣经
Data Visualization with R[49]：R语言实战的作者的另一个作品
R Gallery Book[50]：The R Graph Gallery[51]的完整指南
Beyond Multiple Linear Regression[52]：回归分析的拓展：广义线性模型和分层模型
Applied longitudinal data analysis in brms and the tidyverse[53]：纵向数据分析
Interpretable Machine Learning[54]：可解释机器学习
现代应用统计与R语言[55]：顾名思义
R语言教程[56]：同上
统计计算[57]：同上
零基础学R语言[58]：同上
Rmd权威指南[59]：by谢大大
Rmd中文指南[60]：这本似乎还未完待续
blogdown[61]：谢大大用R写博客
bookdown[62]：谢大大用R写书
电子书、在线课程、教程
生物统计手册：Handbook of Biological Statistics[63] 以及它的R陪同：An R Companion for the Handbook of Biological Statistics[64]
部分免费的数据科学课程：DataCamp[65]、Dataquest[66]、Datanovia[67]
Biomedical Data Science[68]：生物医学数据科学
Introduction to Econometrics with R[69]：R语言计量经济学导论（量：第四声）
Forecasting: Principles and Practice (3rd ed)[70]：旨在全面介绍预测方法
以下两本是统计学习圣经：
An Introduction to Statistical Learning\(1 ed.\)[71]：ISLR第一版(2021年夏季出第二版：官网[72])
The Elements of Statistical Learning[73]：ESL官网
3.R Packages
Awesome R[74]：优秀的R包和资料
tidyverse[75]、tidymodels[76]：分别代表数据分析、统计模型的一套流程
ggplot2[77] & its 82 extensions[78]：可视化领域的少林
shiny[79]：交互、可视化、分析平台(它的画廊[80])
plotly[81]：可视化另一佳作
htmlwidgets for R[82]：126个HTML图形插件
R任务视图[83]：包含了四十多个热门主题，每个主题下面都有几十个包供你选择
xaringan[84]：谢大大用R写ppt英文模板[85]、中文模板[86]
R数据集：R自带的datesets[87] package、更全的Rdatasets[88]（不是package，只是含有dataset的package的信息）
4.Others
R官方文档[89]、R贡献文档[90]
timeline-of-statistics.pdf[91]：简明统计学史(by ASA)
RStudio的cheatsheet[92]：快速回顾一些R包的基本语法(支持邮件订阅；鼓励大家参与到该网址中的中文翻译项目；当然除了由RStudio发布的cheatsheet，还有其他机构也会发布，比如DataCamp的cheatsheet[93]，其中还有Python的)
帮助自学：
UCB统计系推荐阅读清单[94]
ASA的统计学本科课程大纲[95]
阅读材料：
Statistical Science Conversations[96]：IMS的与一百多位统计学家的访谈专栏
How R Helps Airbnb Make the Most of its Data[97]
Why Is It Called That Way\?\! – Origin and Meaning of R Package Names[98]：一些R包名称的由来
Tidy Data[99]：by Hadley Wickham
未完待续.
参考资料
[1]
CoffeeCat:
https://www.zhihu.com/people/CoffeeCat2000
[2]
Coffee学生物统计的地方:
https://www.zhihu.com/column/c_1242033096192262144
[3]
北大李东风:
https://link.zhihu.com/?target=https%3A//www.math.pku.edu.cn/teachers/lidf/
[4]
中科大张伟平:
https://link.zhihu.com/?target=http%3A//staff.ustc.edu.cn/~zwp/teach.htm
[5]
谢益辉:
https://link.zhihu.com/?target=https%3A//yihui.org/
[6]
统计之都论坛:
https://link.zhihu.com/?target=https%3A//d.cosx.org/
[7]
统计之都:
https://link.zhihu.com/?target=https%3A//cosx.org/
[8]
统计学资源链接大全:
https://link.zhihu.com/?target=http%3A//staff.ustc.edu.cn/~ynyang/stat-resources.html
[9]
该老师的主页:
https://link.zhihu.com/?target=http%3A//staff.ustc.edu.cn/~ynyang
[10]
Trevor Hastie:
https://link.zhihu.com/?target=http%3A//www-stat.stanford.edu/~hastie/
[11]
Jerome H. Friedman:
https://link.zhihu.com/?target=http%3A//statweb.stanford.edu/~jhf/
[12]
Rob Tibshirani:
https://link.zhihu.com/?target=http%3A//statweb.stanford.edu/~tibs/
[13]
顾凯:
https://link.zhihu.com/?target=https%3A//www.bioinfo-scrounger.com/
[14]
revolutionanalytics:
https://link.zhihu.com/?target=https%3A//blog.revolutionanalytics.com/
[15]
r-bloggers:
https://link.zhihu.com/?target=https%3A//www.r-bloggers.com/
[16]
Statistics How To:
https://link.zhihu.com/?target=https%3A//www.statisticshowto.com/
[17]
Statistical Modeling, Causal Inference, and Social Science:
https://link.zhihu.com/?target=https%3A//statmodeling.stat.columbia.edu/
[18]
Error Statistics Philosophy:
https://link.zhihu.com/?target=https%3A//errorstatistics.com/
[19]
Simply Statistics:
https://link.zhihu.com/?target=https%3A//simplystatistics.org/
[20]
Jeff Leek:
https://link.zhihu.com/?target=http%3A//www.biostat.jhsph.edu/~jleek/research.html
[21]
Roger Peng:
https://link.zhihu.com/?target=http%3A//www.biostat.jhsph.edu/~rpeng/
[22]
Rafa Irizarry:
https://link.zhihu.com/?target=http%3A//rafalab.dfci.harvard.edu/
[23]
FLOWINGDATA:
https://link.zhihu.com/?target=https%3A//flowingdata.com/
[24]
Statistics by Jim:
https://link.zhihu.com/?target=https%3A//statisticsbyjim.com/
[25]
Library Genesis:
https://link.zhihu.com/?target=http%3A//libgen.rs/
[26]
亚马逊:
https://link.zhihu.com/?target=http%3A//amazon.com/
[27]
Routledge:
https://link.zhihu.com/?target=https%3A//www.routledge.com/
[28]
Chapman & Hall/CRC Texts in Statistical Science:
https://link.zhihu.com/?target=https%3A//www.routledge.com/Chapman--HallCRC-Texts-in-Statistical-Science/book-series/CHTEXSTASCI
[29]
Chapman & Hall/CRC Biostatistics Series:
https://link.zhihu.com/?target=https%3A//www.routledge.com/Chapman--HallCRC-Biostatistics-Series/book-series/CHBIOSTATIS
[30]
Springer:
https://link.zhihu.com/?target=https%3A//www.springer.com/
[31]
Springer Statistics:
https://link.zhihu.com/?target=https%3A//www.springer.com/gp/statistics
[32]
Elsevier:
https://link.zhihu.com/?target=https%3A//www.elsevier.com/
[33]
Oxford University Press:
https://link.zhihu.com/?target=https%3A//global.oup.com/academic/%3Fcc%3Dus%26lang%3Den%26
[34]
Probability & Statistics:
https://link.zhihu.com/?target=https%3A//global.oup.com/academic/category/science-and-mathematics/mathematics/probability-and-statistics/%3Fcc%3Dus%26lang%3Den%26
[35]
Cambridge University Press:
https://link.zhihu.com/?target=https%3A//www.cambridge.org/cn/academic
[36]
Statistics and probability:
https://link.zhihu.com/?target=https%3A//www.cambridge.org/cn/academic/subjects/statistics-probability/
[37]
Bookdown:
https://link.zhihu.com/?target=https%3A//bookdown.org/home/archive/
[38]
数据科学中的R语言:
https://link.zhihu.com/?target=https%3A//bookdown.org/wangminjie/R4DS/
[39]
R语言忍者秘籍:
https://link.zhihu.com/?target=https%3A//bookdown.org/yihui/r-ninja/
[40]
现代统计图形:
https://link.zhihu.com/?target=https%3A//bookdown.org/xiangyun/msg/
[41]
Statistics Handbook:
https://link.zhihu.com/?target=https%3A//bookdown.org/mpfoley1973/statistics/
[42]
R for Data Science:
https://link.zhihu.com/?target=https%3A//bookdown.org/roy_schumacher/r4ds/
[43]
Hadley Wickham: https://link.zhihu.com/?target=http%3A//hadley.nz/
[44]
tidyverse:
https://link.zhihu.com/?target=https%3A//www.tidyverse.org/packages/
[45]
Advanced R:
https://link.zhihu.com/?target=https%3A//adv-r.hadley.nz/
[46]
Hadley Wickham:
https://link.zhihu.com/?target=http%3A//hadley.nz/
[47]
习题解答:
https://link.zhihu.com/?target=https%3A//advanced-r-solutions.rbind.io/
[48]
R Graphics Cookbook:
https://link.zhihu.com/?target=https%3A//r-graphics.org/
[49]
Data Visualization with R:
https://link.zhihu.com/?target=https%3A//rkabacoff.github.io/datavis/
[50]
R Gallery Book:
https://link.zhihu.com/?target=https%3A//bookdown.org/content/b298e479-b1ab-49fa-b83d-a57c2b034d49/
[51]
The R Graph Gallery:
https://link.zhihu.com/?target=https%3A//www.r-graph-gallery.com/
[52]
Beyond Multiple Linear Regression:
https://link.zhihu.com/?target=https%3A//bookdown.org/roback/bookdown-BeyondMLR/
[53]
Applied longitudinal data analysis in brms and the tidyverse:
https://link.zhihu.com/?target=https%3A//bookdown.org/content/ef0b28f7-8bdf-4ba7-ae2c-bc2b1f012283/
[54]
Interpretable Machine Learning:
https://link.zhihu.com/?target=https%3A//christophm.github.io/interpretable-ml-book/
[55]
现代应用统计与R语言:
https://link.zhihu.com/?target=https%3A//bookdown.org/xiangyun/masr/
[56]
R语言教程:
https://link.zhihu.com/?target=https%3A//www.math.pku.edu.cn/teachers/lidf/docs/Rbook/html/_Rbook/index.html
[57]
统计计算:
https://link.zhihu.com/?target=https%3A//www.math.pku.edu.cn/teachers/lidf/docs/statcomp/html/_statcompbook/index.html
[58]
零基础学R语言:
https://link.zhihu.com/?target=https%3A//bookdown.org/qiyuandong/intro_r/
[59]
Rmd权威指南:
https://link.zhihu.com/?target=https%3A//bookdown.org/yihui/rmarkdown/
[60]
Rmd中文指南:
https://link.zhihu.com/?target=https%3A//bookdown.org/qiushi/rmarkdown-guide/
[61]
blogdown:
https://link.zhihu.com/?target=https%3A//bookdown.org/yihui/blogdown/
[62]
bookdown:
https://link.zhihu.com/?target=https%3A//bookdown.org/home/about/
[63]
Handbook of Biological Statistics:
https://link.zhihu.com/?target=http%3A//www.biostathandbook.com/
[64]
An R Companion for the Handbook of Biological Statistics:
https://link.zhihu.com/?target=https%3A//rcompanion.org/rcompanion/index.html
[65]
DataCamp:
https://zhuanlan.zhihu.com/p/366590161/www.datacamp.com
[66]
Dataquest:
https://link.zhihu.com/?target=https%3A//www.dataquest.io/
[67]
Datanovia:
https://link.zhihu.com/?target=https%3A//www.datanovia.com/en/
[68]
Biomedical Data Science:
https://link.zhihu.com/?target=http%3A//genomicsclass.github.io/book/
[69]
Introduction to Econometrics with R:
https://link.zhihu.com/?target=https%3A//www.econometrics-with-r.org/
[70]
Forecasting: Principles and Practice (3rd ed):
https://link.zhihu.com/?target=https%3A//otexts.com/fpp3/index.html
[71]
An Introduction to Statistical Learning(1 ed.):
https://link.zhihu.com/?target=https%3A//www.statlearning.com/s/ISLRSeventhPrinting.pdf
[72]
官网:
https://link.zhihu.com/?target=https%3A//www.statlearning.com/
[73]
The Elements of Statistical Learning:
https://link.zhihu.com/?target=https%3A//web.stanford.edu/~hastie/ElemStatLearn/
[74]
Awesome R:
https://link.zhihu.com/?target=https%3A//github.com/qinwf/awesome-R/blob/master/README.md
[75]
tidyverse:
https://link.zhihu.com/?target=https%3A//www.tidyverse.org/packages/
[76]
tidymodels:
https://link.zhihu.com/?target=https%3A//www.tidymodels.org/packages/
[77]
ggplot2:
https://link.zhihu.com/?target=https%3A//ggplot2.tidyverse.org/
[78]
its 82 extensions:
https://link.zhihu.com/?target=https%3A//exts.ggplot2.tidyverse.org/gallery/
[79]
shiny:
https://link.zhihu.com/?target=https%3A//shiny.rstudio.com/
[80]
它的画廊:
https://link.zhihu.com/?target=https%3A//shiny.rstudio.com/gallery/
[81]
plotly:
https://link.zhihu.com/?target=https%3A//plotly.com/r/
[82]
htmlwidgets for R:
https://link.zhihu.com/?target=https%3A//gallery.htmlwidgets.org/
[83]
R任务视图:
https://link.zhihu.com/?target=https%3A//cran.r-project.org/web/views/
[84]
xaringan:
https://link.zhihu.com/?target=https%3A//github.com/yihui/xaringan
[85]
英文模板: https://link.zhihu.com/?target=https%3A//slides.yihui.org/xaringan/
[86]
中文模板:
https://link.zhihu.com/?target=https%3A//slides.yihui.org/xaringan/zh-CN.html
[87]
datesets:
https://link.zhihu.com/?target=https%3A//stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html
[88]
Rdatasets:
https://link.zhihu.com/?target=https%3A//vincentarelbundock.github.io/Rdatasets/articles/data.html
[89]
R官方文档:
https://link.zhihu.com/?target=https%3A//www.r-project.org/other-docs.html
[90]
R贡献文档:
https://link.zhihu.com/?target=https%3A//cran.r-project.org/other-docs.html
[91]
timeline-of-statistics.pdf:
https://link.zhihu.com/?target=http%3A//www.statslife.org.uk/images/pdf/timeline-of-statistics.pdf
[92]
RStudio的cheatsheet:
https://link.zhihu.com/?target=https%3A//www.rstudio.com/resources/cheatsheets/
[93]
DataCamp的cheatsheet:
https://link.zhihu.com/?target=https%3A//www.datacamp.com/community/data-science-cheatsheets
[94]
UCB统计系推荐阅读清单:
https://link.zhihu.com/?target=http%3A//sgsa.berkeley.edu/current_students/books/
[95]
ASA的统计学本科课程大纲:
https://link.zhihu.com/?target=http%3A//www.amstat.org/education/pdfs/guidelines2014-11-15.pdf
[96]
Statistical Science Conversations:
https://link.zhihu.com/?target=https%3A//imstat.org/journals-and-publications/statistical-science/conversations/
[97]
How R Helps Airbnb Make the Most of its Data:
https://link.zhihu.com/?target=https%3A//www.tandfonline.com/doi/full/10.1080/00031305.2017.1392362
[98]
Why Is It Called That Way?! – Origin and Meaning of R Package Names:
https://link.zhihu.com/?target=https%3A//www.statworx.com/en/blog/why-is-it-called-that-way-origin-and-meaning-of-r-package-names/
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