Wednesday 22 April 2026 9:30am
Research Informatics Training Room, Craik-Marshall Building
About
Date: Wed 22 April 2026
Time: 09:30 - 17:30
Location: Research Informatics Training Room, Craik-Marshall Building
♿ The training room is located on the first floor and there is currently no wheelchair or level access.
Participants can make use of the computers in the training room, unless otherwise advised. Instructions on specific system requirements and downloads will be provided when a booking is secured.
Please ensure you meet the target audience criteria and prerequisites before registering for a course.
Description
Generalised linear models are the kind of models we would use if we had to deal with non-continuous response variables. For example, this happens if you have count data or a binary outcome.
This course aims to introduce generalised linear models, using the R software environment. Similar to Core statistics this course addresses the practical aspects of using these models, so you can explore real-life issues in the biological sciences. The Generalised linear models course builds heavily on the knowledge gained in the core statistics sessions, which means that the Core statistics course is a firm prerequisite for joining.
There are several aims to this course:
1. Be able to distinguish between linear models and generalised linear models
2. Analyse binary outcome and count data using R
3. Critically assess model fit
R is an open-source programming language so all of the software we will use in the course is free. We will be using the R Studio interface throughout the course. Most of the code will be focussed around the tidyverse and tidymodels packages, so a basic understanding of the tidyverse syntax is essential.
How to book Target audience- This course is - in abbreviated form - included as part of several DTP and MPhil programmes, as well as other departmental training within the University of Cambridge (potentially under a different name) so participants who have attended statistics training elsewhere should check before applying.
- This course requires users to be familiar with the R language. Attending an introductory course Data analysis in R is advantageous if you do not have a working knowledge of R already.
- Participants need to have attended the Core statistics course.
- Familiarity with the tidyverse syntax is essential.
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If you are unsure whether you have sufficient knowledge, please do not hesitate to contact us and we will be able to discuss this.
Fees must be paid at registration.
Free for registered University of Cambridge students
£ 65/full day for all University of Cambridge staff, including postdocs.
£ 65/full day for all academic participants from external Institutions and charitable organizations.
£ 130/full day for all Industry participants.
For further information about the courses, please email the Research Informatics Training Team.