- R and RStudio-related cheatsheets: https://www.rstudio.com/resources/cheatsheets/
- R for Data Science, excellent free online book by Garrett Grolemund and Hadley Wickham: http://r4ds.had.co.nz/
- R for Reproducible Scientific Analysis, two introduction materials to R by The Carpentries: https://swcarpentry.github.io/r-novice-gapminder/ and https://datacarpentry.org/R-ecology-lesson/
- Why use R over Excel for your analyses? An R tutorial using the Tidyverse: https://www.jessesadler.com/post/excel-vs-r/
- RStudio's Online Learning page lists useful resources: https://www.rstudio.com/online-learning/
- CRAN's basic and advanced manuals: https://cran.r-project.org/manuals.html
- Lots of quality tutorials on STHDA: http://www.sthda.com/english/
- Lots of quality tutorials on Quick-R: https://www.statmethods.net/index.html
- Lots of quality tutorials on Cookbook for R: http://www.cookbook-r.com/
- LinkedIn Learning R courses: https://www.linkedin.com/learning/topics/r (use your UQ credentials)
- Many excellent books on Bookdown.org: https://bookdown.org/
- Text Analysis focused tutorials by LADAL: https://ladal.edu.au/tutorials.html
- Solve challenges and learn from other people's solutions: https://exercism.org/tracks/r
swirlis a package that allows you to learn R interactively in an R session: https://swirlstats.com/
- The R Graph Gallery for categorised examples and code: https://www.r-graph-gallery.com/
- Interactive web-based data visualization with R, plotly, and shiny, free online book by Carson Sievert: https://plotly-r.com/
- For R programming: http://stackoverflow.com/questions/tagged/r
- About statistics specifically: https://stats.stackexchange.com/questions/tagged/r
- Packages from CRAN, Bioconductor and GitHub: http://www.rdocumentation.org/
- Packages from CRAN, Bioconductor, R-Forge and GitHub; run R code online: https://rdrr.io/
- Daily news and tutorials on R-bloggers: https://www.r-bloggers.com/
- R Weekly's digest of R news: https://rweekly.org/
- Tidyverse (and Tidymodels) news: https://www.tidyverse.org/blog/
- See the next sessions at the Library: https://web.library.uq.edu.au/library-services/training
- If you need assistance via email, or would like to organise a 1-on-1 consultation, please contact our team: training@library.uq.edu.au
- Join the monthly UQ R User Group (UQRUG) to collaborate and share with other R users (every third Monday of the month, 3-5 pm)
- Ask questions to other researchers during the weekly Hacky Hour (Tuesdays at 3 pm, Café Nano, St Lucia): https://rcc.uq.edu.au/meetups
- Meet other R users at the monthly R Peer Group (QIMR Berghofer, Herston). Contact Dwan Vilcins for RSVP and questions.
- QCIF offers introductory programming and advanced statistics workshops: https://www.qcif.edu.au/training/training-courses/
- Contact your unit's statistician