p-hacking

Tutorial: P-hacking

SETUP

All software necessary can be found in installation.md.

Additional requirements

• Memory: The downloaded data needs around 700 MB on your harddrive.

As preparation we recommend to have a look at the resources list in installation.md.

TUTORIAL

soon to come...

Analyse the data with Jupyter Notebook

The analysis of the extracted data is done with Python in a Jupyter Notebook. There are several methods applied. Some of them are descriptive and show the wanted outcome, but some are explorativ, and conclusions must be done by a domain expert by exploring the data and its presentation by her/himselves. The following analysis is done:

Get the Jupyter Notebook: tutorial-p-hacking.ipynb.

Use the Jupyter Notebook:

Go to the tutorials/p-hacking/ folder and start jupyter via:

jupyter notebook

This should let your browser open a new tab with the actual directory in it. Click on the tutorial-systematic-literature-review.ipynb file to open the jupyter notebook. Then you can execute cell by cell and adapt the notebook to your needs. There is a more detailed description of the analysis done in the Jupyter notebook.

FOLLOW UPS

• Do another tutorial from the FutureTDM project: Zika and Libraries
• Learn more about the tools used with our software tutorials
• Contribute to this repository
• Send us your results at Discourse
• Share the tutorial with others in your department or social network.
• Ask us your questions at Discourse, via Email (contact@contentmine.org) or on Twitter (@TheContentMine)

RESSOURCES

All materials worked out in this repository where conducted within the EU Horizon2020 project Future TDM - The Future of Text and Data Mining, an EU Horizon2020 research project with participation of Open Knowledge International and ContentMine.

All content and data is licensed under the Creative Commons Attribution 4.0 International License. All code is under the MIT license.