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Reproducible analysis (1 of 2) with knitr, R Markdown, and RStudio by Dr Jeromy Anglim

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Published on Jul 18, 2012

Video Part 1 of 2: http://youtu.be/XqzHnYLr5BE
Video Part 2 of 2: http://youtu.be/XqzHnYLr5BE

Repository with code examples: https://github.com/jeromyanglim/rmark...

PDF of slides: https://github.com/jeromyanglim/rmark...

Reproducible analysis represents a process for transforming text, code, and data to produce reproducible artefacts including reports, journal articles, slideshows, theses, and books. Reproducible analysis is important in both industry and academic settings for ensuring a high quality product. R has always provided a powerful platform for reproducible analysis. However, in the first half of 2012, several new tools have emerged that have substantially increased the ease with which reproducible analysis can be performed. In particular, knitr, R Markdown, and RStudio combine to create a user-friendly and powerful set of open source tools for reproducible analysis.

This talk will provide an introduction to Markdown and using knitr and R Markdown to produce reproducible reports. In partiuclar, it will discuss caching slow analyses, producing attractive plots and tables, and using RStudio as an IDE. The talk will also show how the markdown package on CRAN can be used to work with other R development environments and workflows for report production. If time permits, the talk may touch on how knitr can be used with other markup languages including LaTeX and HTML.

Jeromy Anglim is a Post Doctoral Fellow in the Melbourne Business School. He has spent the last 10 years teaching statistics in university settings. He has also worked as a statistical consultant in market research, selection and recruitment, and organisational climate survey research. He has been using R for the last five years and regularly blogs about the power of R at http://jeromyanglim.blogspot.com

Relevant links:

knitr: http://yihui.name/knitr/
RStudio: http://rstudio.org/
Markdown: http://daringfireball.net/projects/ma...
R Markdown: http://jeromyanglim.blogspot.com.au/2...
R Reproducible Analysis: http://cran.r-project.org/web/views/R...

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