Date: 27 July 2022 @ 08:30 - 16:00

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This course will be run as an in-person event only!

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 using R 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 using R'' course builds heavily on the knowledge gained in the core statistics sessions, which means that the Core statistics using R 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.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.''

Keywords: HDRUK

Venue: Craik-Marshall Building

City: Cambridge

Country: United Kingdom

Postcode: CB2 3AR

Organizer: University of Cambridge

Host institutions: University of Cambridge Bioinformatics Training

Target audience: Graduate students, Postdocs and Staff members from the University of Cambridge, Institutions and other external Institutions or individuals, 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.

Event types:

  • Workshops and courses


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