Course selection
Introduction to Statistics for the Humanities and Digital Humanities Part 1
Audience: Academic staff, PG research, Research staff
Date: Friday 12 September 2025 to Tuesday 30 June 2026
Times: 11.54
Key details: Introduction to Statistics for the Humanities and Digital Humanities is a new course designed specifically for University of St Andrews research degree students (see eligibility advice below) and staff working in the humanities.
Target audience
The course is open to University of St Andrews staff and students matriculated on a doctoral degree or the following research degree programmes – MSc (Res), MSt (Res), and MPhil (by research). It is aimed at those working and studying in the humanities.
Qualifications needed
There are no pre-requisites for participants enrolling for this course. Some prior knowledge of R/RStudio would be helpful but this will be introduced during the course.
Course pre-work
It would be helpful if R and RStudio are installed on your laptop before the course starts; guidance will be provided after enrolling for the course and in the introductory session.
Course information
The aim of this course is to introduce basic statistical concepts and analysis methods suitable for the humanities and introduce ways in which statistics can be used by scholars of the humanities. The focus is on practical application of statistics, rather than theory, and uses R/RStudio to implement the methods. The course lasts for one semester and introduces the basics of probability and some simple tests. A follow-up course concentrating on applications occurs in semester 2.
The course is facilitated by St Leonard's Postgraduate College and the Centre for Educational Enhancement and Development (CEED) and delivered by the Centre for Research into Ecological and Environmental Modelling (CREEM).
Aims and objectives
Content and Structure
The course content is divided as follows:
I Introduction to probability and sampling
II Testing hypotheses
III Basic statistical tests
The course includes a substantial practical component and the methods covered will be implemented using the statistical programming language R and user-friendly environment RStudio.
The course runs throughout semester 1 and there will be a guided programme for self-paced study. Course material (lecture notes, exercises and computer practicals) will be available on Moodle.
There will be an in-person introductory session in week 4 (week starting 6 Oct 2025) to get you started and throughout the course there will be online help sessions, and a final in-person session to finish the course. You are encouraged to attend these in-person sessions to meet the tutor and fellow participants and provide feedback. Participation in the help sessions is optional.
The weekly time commitment is anticipated to be about 2-3 hours (working through the course notes and associated computer practical and attending any help session).
There is an option for participants to obtain a certificate by attempting all assessed quizzes and a score of at least 50% obtained for each quiz.
Course provider
St Leonard's Postgraduate CollegeEmail: stlc@st-andrews.ac.uk