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---
title: "Resources"
output:
html_document:
toc: true
toc_float:
collapsed: false
---
### `r knitr::include_graphics("./images/r.png", dpi = 1500)` R
* [R homepage](https://www.r-project.org/)
* [Download R](https://cran.r-project.org/)
* [Quick R (all types of examples)](https://www.statmethods.net/index.html)
* [An Introduction to R](https://cran.r-project.org/doc/manuals/r-release/R-intro.html)
* [*R Programming for Data Science* by Roger D. Peng](https://bookdown.org/rdpeng/rprogdatascience/)
* [*Exploratory Data Analysis with R* by Roger D. Peng](https://bookdown.org/rdpeng/exdata/)
* [*Efficient R programming* by Colin Gillespie
and Robin Lovelace](https://bookdown.org/csgillespie/efficientR/)
* [*Advanced R Development* by Hadley Wickham](https://adv-r.had.co.nz/)
* [*Advanced R Solutions* by Malte Grosser and Henning Bumann](https://bookdown.org/Tazinho/Advanced-R-Solutions/)
* [Roger Peng's Computing for Data Analysis Videos](https://bit.ly/UC5UDc)
* [Learning Statistics/R on youtube](https://flavioazevedo.com/stats-and-r-blog/2016/9/13/learning-r-on-youtube)
* [DataCamp](https://www.datacamp.com/home)
* [Free Code School intro R Course](https://www.codeschool.com/courses/try-r)
* [swirl](https://swirlstats.com) "swirl teaches you R programming and data science interactively, at your own pace, and right in the R console"
* [Why Use Docker with R?](https://www.opencpu.org/posts/opencpu-with-docker/)
### `r knitr::include_graphics("./images/rstudio.jpg", dpi = 1200)` RStudio
* [ASU RStudio Server](https://mathr.appstate.edu/)
* [RStudio (IDE)](https://posit.co/)
* [RStudio Documentation](https://support.posit.co/hc/en-us/categories/200035113-Documentation)
* [RStudio Cheat Sheets](https://posit.co/resources/cheatsheets/)
* [POSIT Cloud](https://posit.cloud/)
### `r knitr::include_graphics("./images/DataCamp.png", dpi = 120)` Data Camp
* [Data Science Courses Using R](https://www.datacamp.com/courses/tech:r)
* [Data Science Courses Using Python](https://www.datacamp.com/courses/tech:python)
### `r knitr::include_graphics("./images/ggplot2.png", dpi = 300)` Graphics
* [R Graphics Cookbook, 2nd edition](https://r-graphics.org/)
* [The `R` Graph Gallery](https://www.r-graph-gallery.com/)
* [`ggplot2`: Elegant Graphics for Data Analysis](https://ggplot2-book.org/)
* [Lattice: Multivariate Data Visualization with R - Figures and code](https://lmdvr.r-forge.r-project.org/figures/figures.html)
* [The Grammar and Graphics of Data Science (Video)](https://www.rstudio.com/resources/webinars/the-grammar-and-graphics-of-data-science/) (58:50)
* [`plotly` for R](https://cpsievert.github.io/plotly_book/)
* [Plotly tutorial: Plotly and R](https://www.datacamp.com/community/open-courses/plotly-tutorial-plotly-and-r)
* [DiagrammeR](https://rich-iannone.github.io/DiagrammeR/)
### `r knitr::include_graphics("./images/shiny.png", dpi = 300)` Shiny Apps
* [Shiny](https://shiny.posit.co/)
* [shinyapps.io server](https://shinyapps.io)
* [Interactive web-based data visualization with R, plotly, and shiny](https://plotly-r.com/)
* [Shiny Apps Documentation](https://docs.posit.co/shinyapps.io/)
* [Shiny Cheatsheet](https://posit.co/resources/cheatsheets/)
* [Building Shiny Apps](https://stat545.com/shiny-tutorial.html)
* [Simulating Confidence Intervals (running on RStudio Shiny Apps server)](https://alanarnholt.shinyapps.io/CISIMG)
* [Normal Distribution Calculator (running on ASU's connect server)](https://mathr.appstate.edu/connect/content/62bcf958-4d89-4d3d-b87a-8a0ba7d4532b)
* [Normal Distribution Calculator (running on RStudio Shiny Apps server)](https://alanarnholt.shinyapps.io/norm_area2/)
* [How to get your very own RStudio Server and Shiny Server with DigitalOcean](https://deanattali.com/2015/05/09/setup-rstudio-shiny-server-digital-ocean/)
* [Building Dashboards with Shiny Tutorial](https://posit.co/resources/videos/building-dashboards-with-shiny-tutorial-joe-cheng/)
* [Dynamic Dashboards with Shiny](https://www.youtube.com/watch?v=tmHh89VTanw)
### `r knitr::include_graphics("./images/devtools.png", dpi = 300)` R Package Building
* [_R Packages_ by Hadley Wickham](http://r-pkgs.had.co.nz/)
* [*Mastering Software Development in R* by Roger D. Peng, Sean Kross, and Brooke Anderson](https://bookdown.org/rdpeng/RProgDA/)
* [`packagedocs`](https://hafen.github.io/packagedocs/)
* [`pkgdown`](https://pkgdown.r-lib.org/)
### `r knitr::include_graphics("./images/dplyr.png", dpi = 300)` Using [`dplyr`](https://cran.r-project.org/web/packages/dplyr/index.html)
* [Introduction to `dplyr` vignette](https://cran.r-project.org/web/packages/dplyr/vignettes/dplyr.html)
* [`dplyr` video1-tutorial](https://www.dataschool.io/dplyr-tutorial-for-faster-data-manipulation-in-r/)
* [`dplyr` video2-tutorial](https://www.dataschool.io/dplyr-tutorial-part-2/)
### `r knitr::include_graphics("./images/knitr.png", dpi = 300)`Reproducible Analysis
* [`knitr` Homepage](https://yihui.org/knitr/)
* [`knitr` Package Development on GitHub](https://github.com/yihui/knitr)
* [*Bookdown: Authoring Books with R Markdown* by Yihui Xie](https://bookdown.org/yihui/bookdown/)
* [*Reproducible Research with* R/RStudio Development on GitHub](https://github.com/christophergandrud/Rep-Res-Book)
* [CRAN views of Reproducible Analysis](https://cran.r-project.org/web/views/ReproducibleResearch.html)
* [Reproducible Reporting (Video)](https://posit.co/resources/videos/reproducible-reporting/) (58:03)
* [*Getting used to R, RStudio, and R Markdown* by Chester Ismay](https://ismayc.github.io/rbasics-book/)
* [*My Final College Paper* by Chester Ismay](https://ismayc.github.io/thesisdown_book/index.html)
* [*A Guide to Reproducible Code in Ecology and Evolution*](https://www.britishecologicalsociety.org/wp-content/uploads/2017/12/guide-to-reproducible-code.pdf)
* [*Good enough practices in scientific computing*](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005510)
### `r knitr::include_graphics("./images/rmarkdown.png", dpi = 300)` R Markdown
* [*R Markdown: The Definitive Guide* by Yihui Xie, J. J. Allaire, and Garrett Grolemund](https://bookdown.org/yihui/rmarkdown/)
* [R Markdown Cookbook](https://bookdown.org/yihui/rmarkdown-cookbook/)
* [R Markdown V2](http://rmarkdown.rstudio.com)
* [Getting started with R Markdown (Video)](https://posit.co/resources/videos/getting-started-with-r-markdown/) (1:02:44)
* [Markdown](https://daringfireball.net/projects/markdown/)
### `r knitr::include_graphics("./images/rmarkdown.png", dpi = 300)` Creating Slides with R
* [R Markdown - ioslides, reveal.js, Slidy, and Beamer](https://bookdown.org/yihui/rmarkdown/ioslides-presentation.html#overview)
* [`xaringan`](https://github.com/yihui/xaringan)
* [R Presentations](https://support.posit.co/hc/en-us/sections/200130218-R-Presentations)
### `r knitr::include_graphics("./images/git.jpg", dpi = 450)` Git
* [*Happy Git and GitHub for the useR* by Jenny Bryan and the STAT 545 TAs](https://happygitwithr.com/)
* [Download Git](https://git-scm.com/)
* [GitHub Help Page](https://help.github.com/)
* [Create a Project](https://gitimmersion.com/lab_03.html)
* [Git Cheatsheet](https://www.ndpsoftware.com/git-cheatsheet.html)
* [Free Code School Intro to Git](https://www.codeschool.com/courses/try-git)
* [Pro Git Book](https://git-scm.com/book)
* [Try Git on GitHub](https://try.github.io/levels/1/challenges/1)
* [Clone a GitHub Repo with RStudio (Video)](https://www.youtube.com/watch?v=YxZ8J2rqhEM) (5:05)
* [Clone a GitHub Repo with RStudio (Slides)](https://github.com/alanarnholt/Homework-Examples/blob/master/Slides/ForkCloneRStudio.pdf)
* [Collaboration and time travel: version control with git, github and RStudio (Video)](https://posit.co/resources/videos/collaboration-and-time-travel-version-control-with-git-github-and-rstudio/) (48:56)
### `r knitr::include_graphics("./images/linux2.png", dpi = 2500)` Using Unix Like Commands
* [Play Terminus to learn basics of the shell](https://web.mit.edu/mprat/Public/web/Terminus/Web/main.html)
* [Michael Stonebank's Unix Tutorial for Beginners](https://www.ee.surrey.ac.uk/Teaching/Unix/)
### Data Science
* [*R for Data Science* by Garrett Grolemund and
Hadley Wickham](https://r4ds.hadley.nz/)
* [*MODERN DIVE: An Introduction to Statistical and Data Sciences via R* by Chester Ismay and Albert Y. Kim](https://moderndive.com/)
* [*Tidy Modeling with R*](https://www.tmwr.org/)
* [*Feature Engineering and Selection: A Practical Approach for Predictive Models* by Max Kuhn and Kjell Johnson](https://bookdown.org/max/FES/)
* [Tidymodels](https://www.tidymodels.org/)
* [*Tidy Text Mining with R* by Julia Silge and David Robinson](https://tidytextmining.com/)
* [*Hands-On Machine Learning with R*](https://bradleyboehmke.github.io/HOML/)
* [*Introduction to Data Science* by Hui Lin and Ming Li](https://scientistcafe.com/ids/)
* [*Introduction to Data Science* by Tiffany-Anne Timbers, Trevor Campbell and
Melissa Lee](https://datasciencebook.ca/)
* [The **caret** Package](https://topepo.github.io/caret/index.html)
* [OnePageR](https://togaware.com/onepager/)
* [*Interpretable Machine Learning* by Christoph Molnar](https://christophm.github.io/interpretable-ml-book/)
* [*Beyond Multiple Linear Regression*](https://bookdown.org/roback/bookdown-BeyondMLR/)
* [*Databricks*---Databricks Community Edition](https://community.cloud.databricks.com/)
### $\LaTeX$
* [Download LaTeX for Macs (TeXLive)](https://tug.org/mactex/)
* [Download LaTeX for Windows (MikTeX)](https://miktex.org/)
* [More Math into LaTeX](https://www.ctan.org/pkg/math-into-latex-4)
* [Getting started with LaTeX](https://www.tug.org/begin.html)
* [LaTeX Wikipedia](https://en.wikipedia.org/wiki/LaTeX)
* [Clever help finding LaTeX symbols](https://detexify.kirelabs.org/classify.html)
### Zotero
* [Using Zotero](https://stat-ata-asu.github.io/STT2810HonorsClassRepo/RMarkdown/ZoteroInClass.html)
### Other Interesting Stuff
* [R-bloggers](https://r-bloggers.com)
* [John Chambers recounts the history of S and R](https://blog.revolutionanalytics.com/2014/01/john-chambers-recounts-the-history-of-s-and-r.html)
* * *