100 个统计学和 R 语言学习资源网站-技术圈

简介

原文：统计学 & R学习资源

编辑：庄闪闪的R语言手册，pythonic生物人

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。如果公众号阅读体验不佳，可以在文末原文链接跳转。

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]:

链接网页上方许多按钮是可以按的，请自行探索

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/

[99]

Tidy Data: https://link.zhihu.com/?target=https%3A//vita.had.co.nz/papers/tidy-data.pdf

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100 个统计学和 R 语言学习资源网站

简介