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。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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