Introduction: towards reproducible science using version control and GNU R

A very short introduction. https://tinyurl.com/repsci

Reproducible science

Reproducibility is "the ability to recompute data analytic results given an observed dataset and knowledge of the data analysis pipeline" (Leek & Peng 2015)

How can we get there?

Quoting (Leek & Peng 2015):

• "the raw data from the experiment are available"
• "the statistical code and documentation to reproduce the analysis are available"
• "correct data analysis must be performed"

Today, we will focus on the second point and explore tools which can help others to understand and reproduce your data analysis.

Note that others may include yourself, 2 months later. ;)

Tools we will get to know:

Click the links for the course materials.

• The version control system Git
• Two R packages that help with reproducible research:
  • apaTables
  • rmarkdown (or the german version)

Gettings a local copy of this repo

If you already have git installed, you can checkout this whole repository:

git clone https://github.com/dfsp-spirit/reproducible_science