Course flyer
This is an online live course.
Dates & times:
- 4-8 May 2026
- 08.30-15.30 (Norwegian time)
This is an onsite course for IMR staff and students, with the option for non-IMR participants to join online via Zoom.
This (live) online course consists of 5 modules representing a total of approximately 40 hours of work. Each module consists of live teaching, followed by exercises using real aquaculture data sets.
The exercises will address key biological and environmental processes affecting aquatic organisms and aquaculture systems, including disease dynamics, host–pathogen interactions, environmental stressors, and the impacts of climate change and human activities on aquatic health and productivity.
The course will also address experimental and study design considerations, such as determining appropriate numbers of cages, fish specimens, and parasite load levels (power analysis).
Brief outline
We begin with an introduction to R and provide a protocol for data exploration to avoid common statistical problems. We will discuss how to detect outliers, deal with collinearity and transformations. An important statistical tool is multiple linear regression. Various basic linear regression topics will be explained from a biological point of view. We will discuss potential problems and show how generalised linear models (GLM) can be used to analyse continuous and presence-absence data.
In the second part of the course, we present an introduction to linear mixed effects models and generalised linear mixed-effects models (GLMM) to analyse hierarchical or clustered data, e.g. multiple observations from the same fish, site, area, cage, tank, lake, transect, etc. These statistical techniques are designed to take care of dependency in your data. GLMMs are applied on continuous, binary (e.g. absence/presence of a disease) and proportional data using the Gaussian, Bernoulli, binomial and beta distribution.
Did you already attend our Data Exploration and Linear Regression course?
You’re welcome to join us for days 3, 4, and 5, where you’ll deepen your skills by learning GLMM modelling using real aquaculture datasets.
Pre-required knowledge
Basic statistics (e.g. mean, variance, normality). No R knowledge is required. You will learn R ‘on the fly’. This is a non-technical course.
1 hour face-to-face
The course includes a 1-hour face-to-face video chat with the instructors (to be used after the course). You are invited to apply the statistical techniques discussed during the course on your own data and if you encounter any problems, you can ask questions during the 1-hour face-to-face chat.
A discussion board (access for 12 months) allows for interaction on course content between instructors and participants.
Course content by day: See flyer
For terms and conditions, see: