12 Continued Learning

Now that you’ve learned about reproducible data analysis in R, you’ll want a list of references to look back on, some tips about where to find help, and some pointers on how to further develop your R skills. One of the great things about open source tools like R, is the abundance of free resources available to help you teach yourself.

12.1 References

• The materials from this course
• RStudio built in documentation (help tab, .etc)
• git-scm.com tutorials and documentation
• cheat-sheets (RStudio -> Help -> Cheatsheets)

12.2 Where to Find Help

• stackoverflow: a great set of websites for finding well vetted answers to specific problems.
• The R Inferno: a humorous and useful exploration of the quirks of R
• aRrgh: a newcomer’s (angry) guide to R: an angry and useful exploration of the same and other quirks

12.3 Other helpful and/or cool stuff

• Jupyter Lab: an alternative to RMarkdown that also works with Python and other programming languages. Part of Project Jupyter.

Fraser, Hannah, Timothy Parker, Shinichi Nakagawa, Ashley Barnett, and Fiona Fidler. 2018. “Questionable Research Practices in Ecology and Evolution.” Open Science Framework. doi:10.17605/OSF.IO/AJYQG.

Hampton, Stephanie E, Sean Anderson, Sarah C Bagby, Corinna Gries, Xueying Han, Edmund Hart, Matthew B Jones, et al. 2015. “The Tao of Open Science for Ecology.” Ecosphere 6 (July). doi:http://dx.doi.org/10.1890/ES14-00402.1.

Ioannidis, John P A. 2005. “Why Most Published Research Findings Are False.” PLoS Medicine 2 (8): e124. doi:10.1371/journal.pmed.0020124.

Ioannidis, John P A, David B Allison, Catherine A Ball, Issa Coulibaly, Xiangqin Cui, Aedín C Culhane, Mario Falchi, et al. 2009. “Repeatability of Published Microarray Gene Expression Analyses.” Nature Genetics 41 (2): 149–55. http://www.ncbi.nlm.nih.gov/pubmed/19174838.

Marwick, Ben. 2017. Rrtools: Creates a Reproducible Research Compendium. https://github.com/benmarwick/rrtools.

Marwick, Ben, Carl Boettiger, and Lincoln Mullen. 2017. “Packaging Data Analytical Work Reproducibly Using R (and Friends).” PeerJ Preprints 5 (August): e3192v1. doi:10.7287/peerj.preprints.3192v1.

Munafò, Marcus R., Brian A. Nosek, Dorothy V. M. Bishop, Katherine S. Button, Christopher D. Chambers, Nathalie Percie du Sert, Uri Simonsohn, Eric-Jan Wagenmakers, Jennifer J. Ware, and John P. A. Ioannidis. 2017. “A Manifesto for Reproducible Science.” Nature Human Behaviour 1 (1): 0021. doi:10.1038/s41562-016-0021.

Open Science Collaboration. 2015. “Estimating the Reproducibility of Psychological Science.” Science 349 (6251): aac4716–aac4716. doi:10.1126/science.aac4716.