We will use visualisation and data analysis in Colaboratory and write part of the report in Authorea maintaining a bibliography \cite{Cressey_2015}. The tables will be in csv from colaboratory, we will write the text in colaboratory and in authorea; some file manipulation will be through github with the web interface; we will create a collaborative data analysis and report writing environment where online and offline research will be possible, including pushing out the report in many different formats. This will also act as a quick primer on python. We will use python 3 for data analysis.

You can launch and download the jupyter notebook from the Authorea servers, work on the notebook and use the notebook to create files and push changes to a git repo that Authorea comes with. The git repo will then allow you to control the contents of the text you will write here. This way the text with citations and tables live here, while the jupyter notebook is where analytical work gets done. If you want, you can keep the jupyter notebook on the github repo and use this as a gist so that your readers can work directly on the web even if they do not have access to a jupyter.