Statistical literacy for the humanities and social sciences
Last updated
Last updated
By Eetu Mäkelä, professor in Digital Humanities (Human Sciences–Computing Interaction) at the University of Helsinki.
This content is not yet complete, in the sense that some sections have not yet been converted from their original lecture slide format into self-contained texts for self-study. Each such section has a header similar to this at the top noting its draft status, as well as a mark in the table of contents below.
People of all levels in the humanities and interpretive social sciences (henceforth abbreviated as human sciences) interested in whether statistical methods might help them in their own work.
Prerequisites: Absolutely none.
The text of this course is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. This means that you are free to use, embed, remix and further develop any part of this course for use in your own course or other material, as long as you aren't doing anything commercial. The only requirement is that you give appropriate credit for this material, provide a link to the license, and indicate if changes were made (see the license for more details).
If you do make use of this material, I'd naturally also appreciate a ping, as well as the possibility to merge any improvements to this version, even if neither of those is actually required by the license.
For access to the source code of this GitBook, please see this GitHub repository.
