{"id":14063211,"url":"https://github.com/Joe-Rstats/Books","last_synced_at":"2025-07-29T14:32:25.072Z","repository":{"id":46332866,"uuid":"225177562","full_name":"Joe-Rstats/Books","owner":"Joe-Rstats","description":"R \u0026 Stats Books and Websites that I think are good.","archived":false,"fork":false,"pushed_at":"2022-07-18T20:57:42.000Z","size":218,"stargazers_count":9,"open_issues_count":0,"forks_count":4,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-12-04T00:32:52.126Z","etag":null,"topics":["data-science","econometrics","education","political-science","r","r-learning","r-stats","rstats","statistics","statistics-websites"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Joe-Rstats.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-12-01T14:46:34.000Z","updated_at":"2024-10-18T06:35:26.000Z","dependencies_parsed_at":"2022-09-19T20:14:57.095Z","dependency_job_id":null,"html_url":"https://github.com/Joe-Rstats/Books","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Joe-Rstats/Books","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Joe-Rstats%2FBooks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Joe-Rstats%2FBooks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Joe-Rstats%2FBooks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Joe-Rstats%2FBooks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Joe-Rstats","download_url":"https://codeload.github.com/Joe-Rstats/Books/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Joe-Rstats%2FBooks/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":267703066,"owners_count":24130463,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-29T02:00:12.549Z","response_time":2574,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","econometrics","education","political-science","r","r-learning","r-stats","rstats","statistics","statistics-websites"],"created_at":"2024-08-13T07:03:08.660Z","updated_at":"2025-07-29T14:32:24.430Z","avatar_url":"https://github.com/Joe-Rstats.png","language":null,"funding_links":[],"categories":["Others"],"sub_categories":[],"readme":"\n# 2022 VERSION FOR LEARNING R\n# Note about Stars\n\n- Three Stars = Excellent\n- Two Stars = Great\n- One Star = Good\n- No Star = Still useful, but save for last\n\n## Learning R\n- [Hands On Programming in R](https://rstudio-education.github.io/hopr/) :star: :star:\n- [Slow R](https://psu-psychology.github.io/r-bootcamp-2019/talks/slow-r.html) :star: :star: :star:\n\n\n\n\n\n\n\n\n\n# R \u0026 Stats Books and Websites that I think are good (2019 Version)\n\n# Note about Stars\n\n- No Star = Good\n- Star = Excellent\n\n## Contents\n- [R with Stats](#R-With-Stats)\n- [R Without Stats](#R-Without-Stats)\n  - [Books](#books)\n    - [Data Visualization Books](#data-visualization-books) \n    - [Coding Books](#Coding-books)   \n      - [R Markdown](#R-Markdown)\n  - [Online Resources](#Online-Resources)\n  - [List of R code](#List-of-R-code)\n    - [Statistical Code](#Statistical-code)\n    - [R Code](#R-code)\n- [Staistics Without R](#statistics-without-r)\n- [Research Design](#Research-design)\n- [Dissertation Websites](#Dissertation-Websites)\n\n## R With Stats\n- [ Math camp] (http://www.csss.washington.edu/academics/math-camp/lectures)\n- [nice courses](https://ditraglia.com)\n- [useful](https://faculty.washington.edu/cadolph/)\n- [Intro to linear regression in R](https://stats.idre.ucla.edu/r/seminars/introduction-to-regression-in-r/)\n- [NYU carpentry - more](https://datacarpentry.org/r-socialsci/) - episodes\n- [NYU carpentry - good] (https://swcarpentry.github.io/r-novice-inflammation/03-loops-R/index.html) - click on episodes.\n- [Intro to R Workshop](https://github.com/UCIDataScienceInitiative/IntroR_Workshop) - :star: good stats stuff here too\n- [R Bootcamp](https://www.jaredknowles.com/r-bootcamp/) - also some good stats tutorials here :star:\n- [UCLA R \u0026 Stats Website](https://stats.idre.ucla.edu/) :star: :star: :star:\n- [University of Cincinnati R programming guide](http://uc-r.github.io) - Click on top left to see all Info. :star:\n- [Using R for introductory econometircs](http://www.urfie.net/read/mobile/index.html#p=1) - SHowing how to do everything in wooldridge in R. :star:\n- [Swirl](https://swirlstats.com)\n- https://iqss.github.io/prefresher/\n- [R Course](https://github.com/jameslamb/teaching/tree/master/mu_rprog)\n- [Advanced quant  methods](https://tvpollet.github.io/PY0794/#course-manual) - The courses (1-11) are very well done. Worth going through the slides and .rmd :star:\n- [R workshops from harvard](https://dss.iq.harvard.edu/workshop-materials#widget-1) - Four short and concise courses. Regression, graphics, data wrangling. :star:\n- [Categorical Regression Models](https://m-clark.github.io/docs/logregmodels.html) :star:\n- [Biol 355/356: Intro to Data Science for Biology](https://biol355.github.io/schedule.html) :star:\n- [GLM](https://rpubs.com/davoodastaraky/GLM) :star:\n- [Learning Statistics With R](https://learningstatisticswithr.com/book/) :star:\n- [Time Series R](https://rpubs.com/bensonsyd/389857) :star:\n- [Simple linear regression](https://rpubs.com/bensonsyd/364877) :star:\n- [more nyu r learning](https://nyu-cdsc.github.io/learningr/):star:\n- [Math Prefresher for poli sci studnets](https://iqss.github.io/prefresher/) :star:\n- [Advanced statistics course](http://statstools.com/learn/advanced-statistics/) :star:\n  - [Notes to accompany the videos](https://osf.io/dnuyv/) :star:\n- [Answering questions with Data](https://crumplab.github.io/statistics/) :star: - Doesn't even get to OLS, but what it does go over, it does well.\n- https://data.princeton.edu/wws509/R\n- [Regression Models for Data science in R](https://leanpub.com/regmods/read#leanpub-auto-poisson-regression):star:\n- [Data Science Specialization Course notes](http://sux13.github.io/DataScienceSpCourseNotes/) - :star:\n- [Statistical Inference for data science](https://leanpub.com/LittleInferenceBook/read) - Very basic, but what it describes, it describes it well. Doesnt even do OLS. :star:\n- [GLM](https://data.princeton.edu/wws509/R) - The R logs are quite good :star:\n- [MSc Conversion in Psychological Studies/Science](https://psyteachr.github.io/msc-conv-f2f/) :star:\n- [Quick-R](https://www.statmethods.net/) :star:\n- [An Introduction to R](http://personality-project.org/r/short_courses/aps-short.pdf) :star:\n- [Data Skills for Reproducible Scinece](https://psyteachr.github.io/msc-data-skills/index.html) - Goes over working with Data and Stats :star:\n- [Interactive data viz](https://plotly-r.com)\n- [Nice R Site](https://preludeinr.com)\n- [Good stuff here](https://github.com/pmaji/data-science-toolkit)\n- https://projects.iq.harvard.edu/gov2001\n- [Organized list of good youtube videos](http://flavioazevedo.com/stats-and-r-blog/2016/9/13/learning-r-on-youtube) :star:\n- [Good youtube series](https://www.youtube.com/channel/UCRJyvz_aLmJLFimTZ9kH1Lg) :star:\n- [Econometrics in R](https://tyleransom.github.io/econometricslabs.html) :star:\n- [Intro to Econometrics with R](https://www.econometrics-with-r.org/) :star:\n- [Logit, probit and multinomial logit in R](https://dss.princeton.edu/training/LogitR101.pdf) :star:\n- [some useful R tutorials here](http://www.econ.uiuc.edu/~econ508/e-ta.html) :star:\n- [Linear Regression with R](https://dss.princeton.edu/training/Regression101R.pdf) :star:\n- [Intro to data analysis](https://github.com/UCIDataScienceInitiative/IDA-with-R) :star:\n- [R and Statistics](http://www.dartistics.com/index.html) :star:\n- [Getting Started in R](https://rcatlord.github.io/GSinR/) :star:\n- [YaRrr the pirates guide to R](https://bookdown.org/ndphillips/YaRrr/) :star:\n- [Interpreting ols output in R](https://feliperego.github.io/blog/2015/10/23/Interpreting-Model-Output-In-R) :star:\n- [Learning Statistics in R](https://ademos.people.uic.edu/index.html) :star:\n- https://data.princeton.edu/R/GLMs\n- [Practical Regression and Anova using R](https://people.bath.ac.uk/jjf23/book/pra.pdf) - Old but seems like it would still be useful.\n- [Interesting book](https://rafalab.github.io/dsbook/random-variables.html)\n- [R course] (https://github.com/uo-ec607/lectures)\n- [Quantitative Research Methods for Political Science, Public Policy and Public Administration: 4th Edition With Applications in R](https://bookdown.org/ripberjt/qrmbook/)\n- [Introduction to Quantitative Methods in R](https://bookdown.org/ejvanholm/Textbook/) - Most advanced it gets is OLS.\n- [Regression analysis in R](https://raw.githack.com/uo-ec607/lectures/master/08-regression/08-regression.html)\n- [Good Econometric Course](https://github.com/edrubin/EC525S19)\n    - Notes (http://edrub.in/ARE212/index.html)\n- [Multiple linear regression R](https://rpubs.com/bensonsyd/385183)\n- [Data analysis and predictin algorithms with r](https://rafalab.github.io/dsbook/)\n- [Using R for Data Analysis and Graphics](https://cran.r-project.org/doc/contrib/usingR.pdf)\n- [Data Analysis and Prediction Algorithms with R](https://rafalab.github.io/dsbook/)\n- [Applied Econometrics with R](https://eeecon.uibk.ac.at/~zeileis/teaching/AER/)-\n- [statstools](http://statstools.com/learn/)\n- [Good Youtube two minute tutorials](https://www.youtube.com/playlist?list=PLcgz5kNZFCkzSyBG3H-rUaPHoBXgijHfC)\n- [Purdue R tutorial](https://www.stat.purdue.edu/scs/docs/R_Introduction.pdf)\n- [Quantitative Analysis - Applied Inferential Statistics](https://slu-soc5050.github.io)\n- http://www.stephenpettigrew.com/r/\n- [Open data science masters](http://datasciencemasters.org)\n- [Modeling Social Data](http://modelingsocialdata.org/syllabus/)\n- [(Very) basic steps to weight a survey sample](https://bookdown.org/jespasareig/Book_How_to_weight_a_survey/)\n- [Step by Step how to analyze public datasets](http://asdfree.com) - includes ANES\n- [Intro to data science](https://rafalab.github.io/dsbook/importing-data.html)\n- [CUrated listed of how to learn R](https://osf.io/be7yt/wiki/Learning%20R/)\n## R Without Stats\n### Books\n#### Coding Books\n- [R for the rest of us](https://rfortherestofus.com/courses/getting-started/)\n -[shiny](https://laderast.github.io/gradual_shiny/)\n- [What they forgot to teach you about R](https://rstats.wtf)\n- [Nice R and data viz courses](https://www.yan-holtz.com/teaching)\n -[ An introduction to data cleaning with R](https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf) :star:\n- [Advanced R](https://adv-r.hadley.nz) :star:\n- [ R Programming for Data Science](https://bookdown.org/rdpeng/rprogdatascience/) :star:\n- [Introduction to Data Science](https://beanumber.github.io/sds192/index.html) :star:\n- [Efficient R programming](https://csgillespie.github.io/efficientR/) :star:\n- [R for data science](https://r4ds.had.co.nz) :star:\n- [Exploratory data analysis with R](https://bookdown.org/rdpeng/exdata/) :star:\n- [R-Data Analysis \u0026 Visualization In Science](https://gge-ucd.github.io/R-DAVIS/index.html) :star:\n- [Intro to R Workshop](https://github.com/UCIDataScienceInitiative/IntroR_Workshop) - :star: good stats stuff here too\n- [R Bootcamp](https://www.jaredknowles.com/r-bootcamp/) - also some good stats tutorials here :star:\n- [some nyu courses](https://guides.nyu.edu/r) -the class materials are good (intro, wrangling, data viz). download the rmarkdown and your good. :star:\n- [An introduction to Data Cleaning with R](https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf) :star:\n- [RStudio Primers](https://rstudio.cloud/learn/primers) :star:\n- [R For Psychological Science](https://psyr.org/) - Goes over basic R stuff, like loops, really well. :star:\n- [an introduction to R for non-programmers](http://swcarpentry.github.io/r-novice-gapminder/) :star:\n- [Programming with R](http://swcarpentry.github.io/r-novice-inflammation/) :star:\n- [Data wrangling, exploration, and analysis with R](https://stat545.com) :star:\n- [Data Cleaning](https://www.kaggle.com/rtatman/data-cleaning-challenge-json-txt-and-xls/) :star:\n- [Data cleaning tricks](https://github.com/underthecurve/r-data-cleaning-tricks) :star:\n- [Hands-On Programming with R](https://rstudio-education.github.io/hopr/) :star:\n- [Github for the R user](https://happygitwithr.com) :star:\n- [Slow Intro to R](https://psu-psychology.github.io/r-bootcamp-2019/talks/slow-r.html) :star:\n- [Intro to R](https://billpetti.github.io/Crash_course_in_R/)\n- [Ton of R courses](https://robchavez.github.io/datascience_gallery/)\n- [An Introduction to R](https://cran.r-project.org/doc/manuals/R-intro.pdf)\n- [Introduction to Data Exploration and Analysis with R](https://bookdown.org/mikemahoney218/IDEAR/)\n- [R for academics](https://bookdown.org/marius_mather/Rad/)\n- [Data science for psychologists](https://bookdown.org/hneth/ds4psy/)\n- [Importing and Cleaning Data in R: Case Studies](https://rpubs.com/williamsurles/291422)\n##### R Markdown\n- [How to start a bookdown book](http://seankross.com/2016/11/17/How-to-Start-a-Bookdown-Book.html)\n- [R for reproducible scientific analysis](http://swcarpentry.github.io/r-novice-gapminder/)\n- [Has some useful R markdown tips](https://cran.r-project.org/web/views/ReproducibleResearch.html)\n- [Manuscripts in Rmarkdown](https://stirlingcodingclub.github.io/Manuscripts_in_Rmarkdown/Rmarkdown_notes.html)- \n- [Youtube Video about R markdown](https://www.youtube.com/watch?v=Nj9J5iCSMB0)\n- [Official R markdown site with tutorial](https://rmarkdown.io.com/index.html)\n- [How to R markdown](http://rpubs.com/collnell/howto_rmd)\n- [topics in R](https://github.com/UCIDataScienceInitiative/Topics_In_R) -some good markdown stuff\n- [R Markdown Basics](https://stats.idre.ucla.edu/r/seminars/r-markdown-basics/)\n- [Slides](https://geocompr.github.io/user_19/presentation/#12)\n- [Markdown tutorial](https://github.com/rstudio-education/communicate-rmd-workshop)\n- [R Markdown video](https://www.youtube.com/watch?v=CHBOVuo6RCo\u0026feature=youtu.be)\n- [bookdown: Authoring Books and Technical Documents with R Markdown](https://bookdown.org/yihui/bookdown/)\n- [Intro to R Markdown](https://m-clark.github.io/Introduction-to-Rmarkdown/)\n- [Pimp my Rmarkdown](https://holtzy.github.io/Pimp-my-rmd/#text_formating)\n- [R Markdown: The definitive guide](https://bookdown.org/yihui/rmarkdown/)\n- [R markdwon for scientists](https://rmd4sci.njtierney.com)\n- [R markdown cookbook](https://bookdown.org/yihui/rmarkdown-cookbook/)\n#### Data Visualization Books\n- [some nyu courses](https://guides.nyu.edu/r) -the class materials are good (intro, wrangling, data viz). download the rmarkdown and your good. :star:\n - [R graphics - an idiots guide](http://rpubs.com/SusanEJohnston/7953):star:\n - [BBC Visual and Data Journalism cookbook for R graphics](https://bbc.github.io/rcookbook/):star:\n- [Fundamentals of Data Visualization](https://serialmentor.com/dataviz/):star:\n- [Data viz book] (http://socviz.co/workgeoms.html#label-outliers)\n### Online Resources\n- [R Tips](http://pj.freefaculty.org/R/Rtips.html) - Basically R FAQ.\n- [Various R tutorials](https://ourcodingclub.github.io/tutorials/)\n- [Package to Teach you R](https://swirlstats.com/)\n- [Rtips](https://twitter.com/rlangtip)\n- [Cool R shiny apps](http://wiki.mgto.org/doku.php/r_shiny_apps)\n- [RWeekly](https://rweekly.org)\n- [CRANberries](http://dirk.eddelbuettel.com/cranberries/about/) - info about new packages\n- [R FAQ](https://stackoverflow.com/questions/tagged/r-faq)\n- [How to get help in R](https://stackoverflow.com/questions/15289995/how-to-get-help-in-r)\n- [Most useful R tricks](https://stackoverflow.com/questions/1295955/what-is-the-most-useful-r-trick)\n- [Useful slack group for questions](https://www.rfordatasci.com/about/)\n- [Stack-Overflow R Resourcees](https://stackoverflow.com/tags/r/info)\n\n\n### List of R Code\n#### Statistical Code\n- [R Codebook](http://www.cookbook-r.com) :star:\n- [R code examples for a number of common data analysis tasks](http://dwoll.de/rexrepos/) - This is very good. Basically shows how to do code for common things we do.:star:\n- [Learn R](https://learnxinyminutes.com/docs/r/):star:\n- [a compendium of r commands to teach statistics](http://mosaic-web.org/go/Master-Core.pdf) :star:\n- [R Functions for Reegression Analysis] (https://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf) :star:\n- [Common R commands used in Data Analysis and Statistical Inference](http://www2.stat.duke.edu/~mc301/R/Rcommands.pdf)\n#### R Code\n- [Good R reference card](https://cran.r-project.org/doc/contrib/Short-refcard.pdf)- :star:\n- [Psychometric Models and Methods](https://cran.r-project.org/web/views/Psychometrics.html)- :star:\n- [How to do Econometric Stats in R](https://cran.r-project.org/web/views/Econometrics.html)- :star:\n- [How to do 604 Stats in R](https://cran.r-project.org/web/views/SocialSciences.html)- :star:\n- [How to deal with missing data in R](https://cran.r-project.org/web/views/MissingData.html)- :star:\n- [How Do I?... In R](https://smach.github.io/R4JournalismBook/HowDoI.html) - :star:\n- [R Cheat Sheet](https://www.sas.upenn.edu/~baron/from_cattell/refcard.pdf)- :star:\n- [R Cheat Sheet](https://cran.r-project.org/doc/contrib/Short-refcard.pdf)- :star:\n- [R \u003c-\u003e Stata](https://www.princeton.edu/~otorres/RStata.pdf)\n- [Modern R with tidyverse](https://b-rodrigues.github.io/modern_R/graphs.html#resources)\n### Statistics Without R\n- [good stuff in courses](https://www3.nd.edu/~rwilliam/)\n- [Math Prefresher for political science students](https://bookdown.org/kuriwaki/prefresher/prefresher.pdf)- :star:\n- [Basic Statistics](https://crumplab.github.io/statistics/foundations-for-inference.html#the-crump-test)- :star:\n- [Advanced Data Analysisfrom an Elementary Point of View](http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ADAfaEPoV.pdf)- :star:\n- [StatTrek](https://stattrek.com)- :star:\n- [Introduction to mathematics for political scientists](http://brendancooley.com/imps2019/)- :star:\n- [Good List of workshops from Cornell](http://www.cscu.cornell.edu/workshops/catalog.php)- :star:\n- [Econometric Academy](https://sites.google.com/site/econometricsacademy/)- :star:\n- [JB statistics](https://www.jbstatistics.com)- :star:\n- [statquest](https://statquest.org/video-index/)- :star:\n- [GLM and multilevel models](https://bookdown.org/roback/bookdown-bysh/)- :star:\n- [Duke Math Camp](http://people.duke.edu/~das76/Mathematics%20for%20Political%20and%20Social%20Research%20Syllabus_Siegel.pdf)- :star:\n\n\n\n\n## other\n- [Machine learning course](https://www.dataschool.io/15-hours-of-expert-machine-learning-videos/)\n- [Version control w git hub, learn it ehre](https://swcarpentry.github.io/git-novice/)\n- [Links to r resources](https://awesomeopensource.com/projects/r?categoryPage=2)\n - [Courses](https://docs.google.com/spreadsheets/d/1LtaeWPzEhRiy-kdNZBn0gPwc6aTYkWtt6Cau6PzcXuo/edit#gid=0)\n - [600 R websites](https://www.datasciencecentral.com/profiles/blogs/600-websites-about-r)\n - [ML tutorioal](https://koalaverse.github.io/machine-learning-in-R/)\n## Research Design\n- [Research design course from LSE](https://thomasleeper.com/designcourse/)\n\n## Dissertation Websites\n- [Advice](https://github.com/edrubin/Advice)\n- [Writing your thesis with r markdown](https://paulvanderlaken.com/2017/09/01/writing-your-thesis-with-r-markdown-1-getting-started/)\n- [Dissertating with Bookdown](https://bookdown.org/thea_knowles/dissertating_rmd_presentation/nitty-gritty-stuff.html#predefined-functions)\n- [One year to dissertate](https://livefreeordichotomize.com/2018/09/14/one-year-to-dissertate/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FJoe-Rstats%2FBooks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FJoe-Rstats%2FBooks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FJoe-Rstats%2FBooks/lists"}