Seminar series and workshops

Last changed: 22 December 2023

Statistics@SLU gives seminar series and workshops on statistical modelling topics.

If you have suggestions for forthcoming topics contact a statistician at your campus or the Centre (

2021 - Environmental Statistics

Seminar serie: Environmental Statistics

August 27, Claudia von Brömssen, SLU: Statistical methods for evaluation of temporal trends in environmental data. Recorded seminar

September 10, James Weldon, SLU:  Change, stability and atmospheric pollutant effects in European forest vegetation (Defense of doctoral thesis)

September 17, Xin Zhao, SLU: Design-based sampling methods for environmental monitoring (Defense of doctoral thesis)

September 24, Arne Pommerening, SLU: Individual-based tree modelling for remote sensing data.

October 1, Jesper Rydén, SLU: Modelling extreme values: problems and concepts

October 15, Martin Sköld, Naturhistoriska riksmuseet, Disentangling effort and density in non-invasive genetic sampling by volunteers, the case of the Swedish Brown Bear monitoring programme

October 22, Annica de Groote, SLU: An introduction to sampling for natural resources

October 29, Anders Grimvall, Havsmiljöinstitutet and Linköpings university: How far can the evaluation of monitoring data be automated?

2020 - The digital SLU

Seminar serie: The digital SLU

August 28: Dorota Anglart, SLU & DeLaval: Generalized additive model for dairy cow somatic cell count predictions using sensor data


September 4: Aakash Chawade, Dept of Plant Breeding, SLU: Challenges and opportunities for analysis of omics data


September 11: Mats Söderström & Kristin Piikki. Dept. of soil and environment: Spatial data for mapping of crop and soil characteristics: Digital soil mapping, modelling crop status from remote sensing data, data fusion, multi-scale modelling, sampling strategies, validation


September 18: Keni Ren, Umeå University: Zoom in on the precision livestock farming


September 25: Måns Thulin, consultant in statistics and AI: An introduction to statistical learning


October 2: Johanna Bergman, AI innovations of Sweden: AI Innovation of Sweden and SLU


October 9: Moudud Alam, Dalarna University: Monitoring reindeer activities in their natural environment


October 16, Johan Holmgren, Dept. for forest resource management, SLU: Forest remote sensing on the individual tree level 


October 23: Bo Stenberg & Johanna Wetterlind, Dept. of soil and environment: Spectral data from proximal sensors for analysis of soil properties: Instruments, data collection, data preparation, modelling, validation

2020 - Machine Learning

Workshop in Machine Learning

The term machine learning hides a variety of different statistical methods. The basic aim of these methods is to recognize or disclose structures / patterns in data. What is often sold a bit like highly complex mathematics usually has simple ideas as a basis.

Some of the theoretical ideas behind machine learning will be presented. However, the focus is on the implementation of these methods in R and the interpretation of the results. In the first part of the workshop, we will deal with continuous response variables, whereas in the second part we will work with category data.

We would like to invite Ph.D. students and researchers to a two-part workshop in R machine learning given by Sven Adler. Part one on 4-5 november (13:00-16:00 and 9:00-12:00), part two on 14-15 december (13:00-16:00 and 9:00-12:00) in Umeå.

Link to Apply

2015 - Mixed models

Workshop in Mixed models


Ulf Olsson: Mixed Models (first day)

Lin Shi, Food Science: The application of mixed model in exploring time dependent postprandial metabolic changes - a randomized, cross-over study (second day)

Andrew Allen, Wildlife, Fish and Environmental Studies: Understanding intraspecific variation in movement patterns of moose: A multi-scale approach (second day)

Wiebke Neumann, Wildlife, Fish and Environmental Studies: Using mixed models to analyze autocorrelated data in nested design. – Examples from the analyses of moose GPS positions across species' latitudinal range (second day)

Johan Pihel, Landscape Architecture, Planning and Management: Mixed effect models in Eye tracking and visual assessment studies of forest landscapes  (second day)

Johannes Forkman, Crop Production Ecology: Randomized block trials with spatial correlation (second day)


Forest data:


Dogs data:


Ladybirds data:


Bayisa data:


2014 - Generalised linear models

2013 - Mixed models

Workshop in Mixed Models


Ulf Olsson: Mixed Models (first day)

Jan-Eric Englund: Does it matter if you use Mixed Models? (second day)

Johannes Forkman: Randomised block trials with spatial korrelation (second day)


Forest data:

Dogs data:

Ladybirds data:


Bayisa data:


Claudia von Brömssen Senior Lecturer at the Department of Energy and Technology; Applied statistics and mathematics

Telephone: 018-671720