Testimonials
Below you will see a list of all our past courses, if you see a course here but can’t find it in the course diary it means we are in the process of scheduling a repeat. If you would like to be notified when a repeat for a specific course has been finalised please email oliverhooker@prstatistics.com

Advances in spatial analysis of multivariate ecological data: theory and practice (MVSP02) 3rd – 7th April 2017

“Attending the Advances in spatial analysis of multivariate ecological data really helped me…”

Tania Bird,
Sand dune ecologist, Ben Gurion University, Israel

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Attending the Advances in Spatial Analysis of Multivariate Ecological Data course really helped me to both understand and apply multivariate stats to my data. I joined the course hoping for guidance and tools to analyse my complex data set for my PhD research on biodiversity trends. The course exceeded my expectations both in terms of how much I learned and how creative and innovative statistics can be!

Pierre Legendre and Olivier Gauthier are truly excellent statisticians but more importantly they are also excellent teachers. I thought I knew the basic theory of ordination covered in the first few days of the course, but the way Pierre explained it shed new light and understanding on these complicated concepts. Although I am not a mathematician, I was able to follow the logic of every analysis, such that I could adapt the methods as needed to my data.

The overall format of the course was well thought out and crammed a lot of information in, starting at the very beginning with basic principles and reaching extremely complex level over just a few days.  Each lecture session was followed by a step by step practical session in the afternoon, allowing us to immediately repeat and apply the theories learned in the morning. I found this an excellent way to learn.

The other great aspect was the range and diversity of the course attendants. We were a very nicely balanced mix of students, researchers, data managers and Professors of all ages, covering a range of marine and terrestrial habitats, and from so many different parts of the world! It made the social aspect really enjoyable and dynamic. In addition the location at Margham Discovery Centre was absolutely stunning and provided much needed fresh air for short breaks and fabulous scenery for long walks in the evenings!

It was very clear that Oliver and his team invest a huge amount of time and effort into perfecting every angle of the course from the teaching quality, specialisation of the topics covered, to the accommodation and location. I am confident that all of the courses conducted by PR Statistics are of similar high standard and enjoyable. I really had great fun learning and would not be able to finish my PhD without this course!

Tania Bird,
Sand dune ecologist, Ben Gurion University, Israel

23 students
17 institutes
12 countries

Alberta University (Canada)

Bournemouth University (England)

Charles University (Czech Republic)

Federal do Rio Grande University – FURG (Brazil)

Ghent University (Belgium)

Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture (IRSTEA) (France)

Institute of Oceanology Polish Academy of Sciences (Poland)

Manitoba University (Canada)

Notre Dame University (USA)

Rhodes University (South Africa)

Royal Belgian Institute of Natural Sciences (Belgium)

Southampton University (England)

University College London (UCL) (England)

Network analysis for ecologists using R (NTWA01) 6th – 10th March 2017

COMING SOON

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 COMING SOON

15 students

12 institutes

10 countries

Åbo Akademi University(Finland)

Aarhus University (Denmark)

Institut Maurice-Lamontagne (Canada)

Institut national de recherche en sciences et technologies (IRSTEA) (France)

Instituto Español de Oceanografía (IEO) (Spain)

Leeds University (England)

Leibniz Centre for Tropical Marine Research (ZMT) Germany)

Mississippi State University (USA)

Senckenberg Biodiversity and Climate Research Centre (Germany)

Stockholm University (Sweden)

Swedish University of Agricultural Sciences (SLU) (Sweden)

Universidade Federal do Rio Grande (FURG) Brazil)

Stable isotope mixing models using SIAR, MixSIAR and SIBER (SIMM03) 28th February – 3rd March 2017

“It was such a pleasure to attend the stable isotope mixing…”

Wilbert Kadye,
Aquatic ecologists, Rhodes University, South Africa

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It was such a pleasure to attend the stable isotope mixing model course. Both Andrew Parnell and Andrew Jackson offered the course at great depth, but were able to skilfully simplify the course content. The course material covered a wide range of topics and concepts that were mostly relevant. In particular, I found the background information helpful in putting the specific topics into perspective. It was also interesting to be introduced to how specific packages work. Overall, the interactions were great, and assistance was timely rendered. Oliver Hooker was absolutely fabulous in making sure that everyone was comfortable both in and outside class. Thank you.”

Wilbert Kadye,
Aquatic ecologists, Rhodes University, South Africa

17 students
13 institutes
9 countries

Alberta University (Canada)

Bournemouth University (England)

Charles University (Czech Republic)

Federal do Rio Grande University – FURG (Brazil)

Ghent University (Belgium)

Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture (IRSTEA) (France)

Institute of Oceanology Polish Academy of Sciences (Poland)

Manitoba University (Canada)

Notre Dame University (USA)

Rhodes University (South Africa)

Royal Belgian Institute of Natural Sciences (Belgium)

Southampton University (England)

University College London (UCL) (England)

Model base multivariate analysis of abundance/presence/absence data using R (MBMV01) 16th – 20th January 2017

COMING SOON

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 COMING SOON

18 students
13 institutes
7 countries

Agroscope (Switzerland)

Ca Foscari University Venice (Italy)

Centre for Ecology and Hydrology (England)

Copenhagen University (Denmark)

DTU Aqua (Denmark)

Environment agency (England)

Essex University (England)

Freie Universität Berlin (Germany)

Lincoln University (England)

Messerli Research Institute/University of Veterinary Medicine of Vienna (Austria)

Natural History Museum (Denmark)

Plymouth University (England)

Wageningen University & Research (Netherlands)

Advancing in statistical modelling using R (ADVR05) 5th – 9th December 2016

COMING SOON

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COMING SOON

24 students
14 institutes
8 countries

Barcelona University (Spain)

Cambridge University (England)

Exeter University (England)

Max Planck Group Odense, University of Southern Denmark (Denmark)

Muséum national d’Histoire naturelle (MNHN) (France)

My Tiny Shinys (Canada)

National Autonomous University of Mexico (UNAM) (Mexico)

Newcastle University (England)

Oxford Brookes University (England)

Plymouth University (England)

Umea University (Sweden)

Universidade Federal do Rio Grande (FURG) (Brazil)

University College London (England)

Spatial analysis of ecological data  using R (SPAE04) 21st – 26th November 2016

COMING SOON

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 COMING SOON

24 students
19 institutes
10 countries

Bangor University (Wales)

Bristol University (England)

College Cork University (Ireland)

Forestry GSI (England)

fRI research (Canada)

Loughborough University (England)

Newcastle University (England)

Norwegian Institute of Bioeconomy Research (Norway)

Oxford Brookes University (England)

Oxford University (England)

Plymouth University (England)

Porto University (CICGE/FCUP) (Portugal)

Rhodes College (USA)

Stanford University (USA)

Swansea University (Wales)

Swedish University of  Agricultural Sciences (Sweden)

Universidade de Sao Paulo (Brazil)

Université de Montréal (Canada)

University of Veterinary Medicine, Hannover (Germany)

Phylogenetic data analysis using R (PHYL01) 31st October – 4th November 2016

COMING SOON

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COMING SOON

10 students
9 institutes
3 countries

Arkansas State University (USA)

Brunel University London (England)

Cornell University (USA)

National Food Institute (DTU Food) (Denmark)

Exeter University (England)

Manchester University (England)

Reading University (England)

Saltford University (England)

Virginia Tech (USA)

Applied Bayesian modelling for ecologists and epidemiologists (ABME02) 24th – 29th October 2016

COMING SOON

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 COMING SOON

20 students
17 institutes
11 countries

Aarhus University (Denmark)

Adelaide University (Australia)

Bern University (Switzerland)

Edinburgh University (Scotland)

Lancaster University (England)

National Food Institute, Technical University of Denmark (Denmark)

Newcastle University (England)

Norwegian Polar Institute (Norway)

Roehampton University (England)

Royal Veterinary College(England)

St Andrews University (Scotland)

Umeå University (Sweden)

University of Veterinary Medicine (Germany)

Vienna University (Austria)

Landscape (population) genetic data analysis using R (LNDG01) 17th – 21st October 2016

COMING SOON

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COMING SOON

21 students
20 institutes
11 countries

Aberdeen University (Scotland)

Ben Gurion University of the Negev (Israel)

Central Florida University (USA)

Copenhagen University (Denmark)

Edge Hill University (England)

Glasgow University (Scotland)

Groningen University (Netherlands)

Leibniz Centre for Agricultural Landscape Research (ZALF) (Germany)

Michigan State University (USA)

Museum für Naturkunde (Germany)

Norwegian University of Science and Technology (Norway)

Oxford University (England)

Potsdam University (German)

Swedish University of  Agricultural Sciences (Sweden)

Tennessee University (USA)

The Graduate Centre CUNY & NYCEP (USA)

Universidad de la Republica (Uruguay)

Zagreb University (Croatia)

Introduction to Bayesian hierarchical modelling (IBHM01) 23rd – 26th August 2016

COMING SOON

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 COMING SOON

10 students
9 institutes
6 countries

Bournemouth University (England)

Fujian Agriculture & Forestry University

German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (Germany)

Glasgow University (Scotland)

Hawaii University (Hawaii)

National Oceanic and Atmospheric Administration (NOAA) (USA)

Newcastle University (England)

Royal Botanic Garden Edinburgh (Scotland)

St Andrews University (Scotland)

Genetic data analysis and exploration using R (GDAR02) 16th – 20th August 2016

COMING SOON

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COMING SOON

21 students
17 institutes
9 countries

British Antarctic Survey (BAS) (England)

Cape Town University (South Africa)

Forest Research  (Scotland)

Freie Universität Berlin (FU Berlin) (Berlin)

Hawaii University (Hawaii)

Imperial College London

Manchester Institute of Biotechnology (England)

Manchester University (England)

Manitoba University (Canada)

Max Planck Institute (Germany)

OUCRU Vietnam (Vietnam)

Royal Botanic Garden Edinburgh/Australian Museum Research Institute (Scotland)

Southampton University (England)

St Andrews University (Scotland)

Statens Serum Institut (Denmark)

Technical University of Denmark (Denmark)

York University (England)

Advances in spatial analysis of multivariate ecological data using R (MVSP01) 11th – 15th July 2016

COMING SOON

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 COMING SOON

30 students
24 institutes
10 countries

Aberdeen University (Scotland)

Bournemouth University (England)

Centre for Ecology and Hydrology (CEH) (England)

Centre for Environment, Fisheries and Aquaculture Science (CEFAS) (England)

Centre national de la recherche scientifique (CNRS) (France)

College Cork University (Ireland)

College London University (England)

Fujian Agriculture & Forestry University

Glasgow University (Scotland)

Imperial College London (England)

Lancaster University (England)

Lausanne University (Switzerland)

Leibniz Center for Tropical Marine Biology (ZMT) (Germany)

National Institute for Environmental and Agricultural Science and Research (IRSTEA) (France)

National Oceanography Centre (England)

New Hampshire University (USA)

Royal Botanic Garden Edinburgh (Scotland)

Southampton University (England)

Stirling University (Scotland)

Wisconsin-Stout University (USA)

Worcester University (England)

Time series models for ecologists and climatologists using R (TSMC01) 10th – 13th May 2016

COMING SOON

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COMING SOON

10 Students
10 different institutes
8 different countries

Arhus University (Denmark)

Bern University (Switzerland)

Centre for Ecology and Hydrology (CEH) (Scotland)

Glasgow University (Scotland)

ICARUS Maynooth University (Ireland)

Liège University (Belgium)

Macquarie University (Australia)

Oldenburg University

Southampton University (England)

Vetmeduni Vienna (Austria)

Advancing in statistical modelling using R (ADVR04) 2nd – 6th May 2016

COMING SOON

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COMING SOON

14 students
12 institutes
6 countries

Centre for Ecology and Hydrology (CEH) (England)

Centre national de la recherche scientifique (CNRS) (France)

College Cork University (Ireland)

College London University (England)

Exeter University (England)

Glasgow University (Scotland)

Greifswald University (Germany)

Macquarie University (Australia)

Stirling University (Scotland)

Stockholm University (Sweden)

Swedish University of Agricultural Sciences (Sweden)

Spatial analysis of ecological data using R (SPAE03) 11th – 17th April 2016

COMING SOON

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COMING SOON

32 students
29 institutes
14 countries

Aberdeen University (Scotland)

Association BIOM (Croatia)

Banyan Tree Global Foundation (Maldives)

British Antarctic Survey (BAS) (England)

British Trust for Ornithology (England)

Centre for Ecology and Hydrology (CEH) (Scotland)

Centre for Marine Futures (Australia)

Centre of Marine Science and Technology (CMST) (Australia)

Conservation Research Africa (Malawi)

Exeter University (England)

Forest research (Scotland)

Freiburg University (Germany)

Glasgow University (Scotland)

Gothenburg University (Sweden)

Greifswald University (Germany)

Leeds University (England)

Macquarie University (Australia)

Marine Scotland (Scotland)

Massachusetts University (USA)

Max-Planck-Institute (Germany)

St Andrews University (Scotland)

Tropical Marine Science Institute (Singapore)

University College London (England)

Universitat de Barcelona (Spain)

Université catholique de Louvain (UCL) (Belgium)

Windsor University (USA)

Stable isotope mixing models using SIAR, MixSIAR and SIBER (SIMM02) 11th – 15th January 2016

COMING SOON
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COMING SOON

27 students
23 institutes
15 countries

Alberta University (Canada)

Alfred Wegener Institute (Germany)

Bournemouth University (England)

Brown University (USA)

Christian-Albrechts-University (Germany)

Cumbria University (Wales)

Glasgow University (Scotland)

Innsbruck University (Austria)

Institute for the Marine and Coastal Environment (Italy)

Instituto de Investigaciones Marinas y Costeras CONICET UNMDP (Argentina)

La Rochelle University (France)

Leibniz Centre for Tropical Marine Ecology (ZMT) (Germany)

Liege University (Belgium)

Liverpool University (England)

Maine Maritime Academy (USA)

Polish Institute of Oceanography (Poland)

Smithsonian Tropical Research Centre (Panama)

Uppsala University (Sweden)

US geological Survey (USA)

Wisconsin-Milwaukee University (USA)

Introduction to statistics and R for biologists (IRFB01) 7th – 11th December 2015

COMING SOON

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COMING SOON

12 students
9 institutes
2 countries

Centre for ecology and hydrology (CEH) (Scotland)

Clyde River Foundation (Scotland)

Freshwater Fisheries Laboratory (Scotland)

Galloway Fisheries Trust (Scotland)

Glasgow University (Scotland)

Liverpool University (England)

The Tweed Foundation (Scotland)

Stirling University (Scotland)

West Sutherland Fisheries Trust (Scotland)

Advancing in statistical modelling using R (ADVR03) 30th November – 4th December 2015

“I wanted a workshop to help me advance in R…”
Aurélien Ginolhac
Bioinformatician, University of Luxembourg
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“I wanted a workshop to help me advance in R that does not skip lectures while giving a large place to hands on session. And that would cover both the practical aspects for R coding AND statistical background. Also, I was hoping for more advanced R than the usual starting point like creating and subsetting vectors. Lastly, I was hoping to find a course organisation that last more than the usual 1 or 2 days, clearly insufficient to get or digest all those informations. I ended up finding this Advanced in R course and cannot find much criticisms.
Luc and Tom were two awesome teachers. Luc gave proper lectures, like 45 minutes in depth explanations before the hands on session. He is relaxed and funny but knows exactly how to provide a sensible way to pass on the stat notions. He spend much time on the linear regression, how to assess the model, what goes on and I think that is a perfect idea. Many more complex stat models are extension of the linear model, understanding completely is then mandatory. Tom is fully aware of the R awesomeness, really up to date with the fast evolving tidyverse ecosystem. He provides a real value to people’s code. Faster, cleaner, better. I am very convinced by the tidyverse and I enjoyed a lot that the provided code for answers was most of time in 2 versions: base and tidyverse. I think as they use Rstudio they should push students to write directly Rmarkdown documents but it might be the case now. So much better for reproducibility and nice outputs.
The content is very progressive. Starting from the linear regression, with one predictor, then 2 and moving out of linearity. The practicals are based on real studies (often from the nice book of Murray Logan) with clear sub-parts. One detail I found very clever, the practicals are provided as 2 full real case studies. An easier one and a supplementary one, more challenging. It allows faster people to not get bored without putting pressure on slower people who can stick to the first practical. Also the audience was from broad origins, in terms of countries but also background and main interest.
Oliver is putting a lot of efforts to make it work, and it just does. Very pragmatic, dedicated to the transmission of knowledge which is the main goal for most people. From fetching the people at the Tullie inn to assigning rooms, things are well organised and transparent for the participants.
Food is prepared right after the courses are done, everyone help to set up tables and afterwards collect dishes. Easy enough. We had a wide choice of beers in the evenings and one evening out to a local pub. I really enjoyed the organisation and the Oliver’ sense of humour!
SCENE allows you to work, eat and sleep at the same place. To me, this is a big advantage. It optimised time while leaving slots for chatting with others and the teachers. Since, this place is pretty remote, most of the people stay there (the all inclusive price is also attractive) and that permit great interactions and warm atmosphere. Also, one can easily finish up some exercises in the evening and teachers are still there to help you. During breaks, the view is scenery, and one can enjoy a walk. I had a really nice experience of feeling quite free to do what I wanted, work in the evening or just relaxed without feeling the pressure to do either of the two.
I think this course, but more broadly, the concept is quite unique. I highly recommend going and learning there, also planning to return for another course next January.”
Aurélien Ginolhac
Bioinformatician, University of Luxembourg

30 students
23 institutes
11 countries

Bangor University (Wales)

Bristol University (England)

Centre for Ecology and Hydrology (England)

Centre for Ecology and Hydrology (Scotland)

Cork University (Ireland)

Durham University (England)

East Anglia University (UEA) (England)

Edinburgh University (Scotland)

Exeter University (England)

Ghent University (Belgium)

Glasgow University (Scotland)

Helsinki University (Finland)

Istituto per la Protezione Sostenibile delle Piante (CNR) (Italy)

Luxembourg University (Luxembourg)

NAFC Marine Centre (Scotland)

National University of Singapore (Singapore)

Oxford University (England)

RijkZwaan Breeding (Netherlands)

St Andrews University (Scotland)

Stirling Univeristy (Scotland)

Strathclyde University (Scotland)

Swedish University of Agricultural Sciences (SLU) (Sweden)

Uppsala University (Sweden)

Spatial analysis of ecological data using R (SPAE02) 16th – 20th November 2015

COMING SOON

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COMING SOON

32 students
22 institutes
13 countries

Aarhus University (Denmark)

Antwerp  University (Denmark)

Bird Life Slovenia (DOPPS) (Slovenia)

Cardiff University (Wales)

Centre for Environment, Fisheries and Aquaculture Science (CEFAS) (England)

Centre national de la recherche scientifique (CNRS) (France)

East Anglia University (UEA) (England)

Exeter University (England)

Fujian Agriculture & Forestry University (China)

Ghent University (Belgium)

Glasgow University (Scotland)

Helsinki University (Finland)

Imperial College London (England)

Institute of Marine Research (Sweden)

Institute of Zootechnics (Italy)

Leibniz Center for Tropical Marine Ecology (Germany)

Oslo University (Sweden)

Plymouth University (England)

Reunion Island (France)

Scottish Rural College (SRUC) (Scotland)

St Andrews University (Scotland)

Swedish University of Agricultural Sciences (Sweden)

 

Applied Bayesian modelling for ecologists and epidemiologists using R (ABME01) 26th – 31st October 2015

COMING SOON

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COMING SOON

30 students
16 institutes
12 countries

Aarhus University (Denmark)

Centre for Ecology and Hydrology (CEH) (Scotland)

Copenhagen University (Denmark)

DARDINI (Northern Ireland)

Glasgow University (Scotland)

Institut national de la recherche agronomique (INRA) (France)

Institute of Advanced Studies in Toulouse (France)

Institute of Tropical Medicine (Belgium)

Kansas University (USA)

Konstanz University (Germany)

Oslo University (Norway)

Scotland Rural College (SRUC) (Scotland)

St Andrews University (Scotland)

Technical University of Denmark (Denmark)

Maryland University (USA)

Uppsala University (Sweden)

Genetic data analysis and exploration using R (GDAR01) 3rd – 7th August 2015

COMING SOON

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COMING SOON

30 students
25 institutes
10 countries

Alfred Wegener Institute (Germany)

Aberdeen University (Scotland)

Bologna University (Germany)

Cambridge University (England)

Centre for Ecology and Hydrology (CEH) (England)

Copenhagen University, (Denmark)

Donana Biological Station (South Africa)

East Anglia University (UEA) (England)

Florida University (USA)

Glasgow University (Scotland)

Helsinki University (Finland)

Highlands University (Scotland)

International Union for the Conservation of Nature (IUCN) (Spain)

Iowa State University (USA)

Leiden University (Austria)

Liverpool University (England)

Nottingham University (England)

Oxford Brookes University (England)

Porto University (Portugal)

Royal Botanic Garden Edinburgh (Scotland)

Sheffield University (England)

St Andrews University (Scotland)

Stirling University (Scotland)

Telemark University College (Norway)

Wien University (Austria)

Stable isotope mixing models using SIAR, MixSIAR and SIBER (SIMM01) 27th – 31st July 2015

“The stable isotope mixing models course was absolutely great…”

Benoit Lebreton,
Assistant professor of marine ecology, University of La Rochelle, France

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“The stable isotope mixing models course was absolutely great. It was high level knowledge provided with very enthusiastic people (i.e., Andrew Jackson and Andrew Parnell). The atmosphere was also very nice between people from the attendance, and it allowed me to meet some people from my field of research and to exchange with them.

The course was very useful as I already knew the methods but as I was missing some technical skills. I was also very helpful as it allowed to discuss the pros and the cons of the different methods with their authors. It gave me more background about how to use these methods and provided me some ideas for my future research.

The instructors were absolutely great. I think it is a real chance to have the possibility to be taught and to exchange with the two persons who invented the methods. Both Andrew Jackson and Andrew Parnell were willing to share. They spent lots of time with me and the other students to talk about our particular cases and our specific questions.

The course was particularly well organised and the facilities were very nice. The location at the Loch Lomond is gorgeous. It allowed to take walks in the evenings to refresh my mind.”

Benoit Lebreton,
Assistant professor of marine ecology, University of La Rochelle, France

30 students
25 institutes
12 countries

Aarhus University (Denmark)

Aberdeen University (Scotland)

British Antartic Survey (BAS) England)

Czech University of Life Sciences (Czech Republic)

The Swiss Federal Institute of Aquatic Science and Technology (EAWAG) (Switzerland)

Ghent University (Belgium)

Glasgow University (Scotland)

Institute of Oceanology Polish Academy of Sciences (Poland)

James Hutton Institute (Scotland)

Koblenz-Landau University (Germany)

Leibniz Institute (Germany)

Nelson Mandela Metropolitan University (South Africa)

Newcastle University (England)

Norwegian Institute for Water Research (Norway)

Plymouth University (England)

Queen Mary University London (England)

Queens University Belfast (Northern Ireland)

Shirshov Institute of Oceanology of Russian Academy of Sciences (Russia)

Stockholm University (Sweden)

The Scottish Universities Environmental Research Centre (SUERC) (Scotland)

Thünen Institute (Germany)

University Koblenz-Landau (Germany)

University of Konstanz (Germany)

University of La Rochelle (France)

Venice University (Italy)

Advancing in Statistical modelling using R (ADVR02) 20th – 24th April 2015

“This was by far the most useful statistic-related course…”

Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England

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“This was by far the most useful statistic-related course I’ve done to date and I enjoyed all aspects of the course. The course was useful because it put into prospective the ecology aspect within the statistics. All parameters were explained in an ecological manner which made the math aspect much clearer. It helped to change the view I’ve got on statistics. I feel like I’ve got a much better understanding of what I should focus on, what I should consider and how to interpret the model outputs. Specific stress was put on to exploring and understanding data prior to doing any modelling, which was a bit of an eye-opener for me.

The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.
Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.

In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.”

Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England

30 students
23 institutes
7 countries

Aarhus University (Denmark)

Aberystwyth University (Wales)

Bangor University (Wales)

Bristol University (England)

British Antarctic Survey (BAS) (England)

Centre for Environment, Fisheries and Aquaculture Science (CEFAS) (England)

Exeter University(England)

Frankfurt University (Germany)

Glasgow University (Scotland)

Helmholtz Centre for Environmental Research (Germany)

Imperial College London (England)

Institute of marine Research (Sweden)

Leeds University (England)

Liege University (Belgium)

Marburg, University (Germany)

Max Plank Institute (Germany)

Nottingham University (England)

Organic Research Centre (Italy)

Oxford University (England)

Royal Belgian Institute of Natural Sciences (Belgium)

Scotland’s Rural College (SRC) (Scotland)

Trento University (Italy)

Université catholique de Louvain (UCL) (Belgium)

Spatial analysis of ecological data using R (SPAE01) 16th – 20th March 2015

“I really enjoyed the Analysis of Spatial Data course…”

Tadhg Carroll
Spatial ecologist, University of Bournemouth, England

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“I really enjoyed the Analysis of Spatial Data course with PR statistics and learned a lot from start to finish. Jason and the other instructors have a great blend of ecological, mathematical and statistical expertise, which showed in a delivery that wove theory and the application of the modelling techniques together really well. It was clear that the course design was well thought through with excellent classes and simulation based practical’s, along with a useful literature archive providing an overview of the many modelling techniques covered and examples of their application. The instructors were happy to answer questions and discuss specific problems that the students had, and I particularly liked the emphasis placed on collaborative problem solving applied to students own study systems and data. I feel that I learned a lot about the scientific process more generally as well as spatial modelling from this aspect of the course. It’s quite a while since I completed the course now and I’m still learning both directly from the course materials and indirectly from the references to the literature provided.

I’d recommend this course to anyone looking for a comprehensive introduction and overview of spatial analytical techniques. I’ve since been back to do three other courses with PR statistics and I think that that in itself will tell you how highly I rate them. The food is great and the remote location promotes a nice atmosphere where you can get to know everyone and have a good laugh in the evenings. Oliver is always helpful and accommodating and he might even sort you with a surprise cheese platter at some point if you’re lucky!”

32 students
16 institutes
7 countries

Aberdeen University (Scotland)

Bangor University (Wales)

British Antarctic Survey (BAS) (England)

Bournemouth University (England)

Centre for Ecology and Hydrology (CEH) (Scotland)

County Cork University (Ireland)

Drexel University (USA), Edinburgh University (Scotland)

Exeter University (England)

Glasgow University (Scotland)

Norwegian University of Science and Technology (Norway)

Scottish Natural Heritage (SNH) (Scotland)

Stirling University (Scotland)

Swiss Ornithological Institute (Switzerland)

University of East Anglia (UEA) (England)

Wetland and Wildfowl Trust (WWT) (England)

Advancing in statistical modelling using R (ADVR01) 1st – 5th December 2014

“I decided to apply for the Advancing in R course…”

Chester Sands
Molecular Ecologist, British Antarctic Survey

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“I decided to apply for the Advancing in R course as I had attended one day R courses in the past but found I had to re learn the basics each time. I thought after an intensive five day course some of the code may stick. And I was right. The course was fairly full, some people wanting to learn R, like me, and others who seemed quite competent in R but wanted to hone specific skills in more complex statistical modelling covered in the last two days of the course.

The instructors were extremely good (personable and patient) and managed to keep the diverse class up to speed every step of the way. Although the first two days were basic introductions to R and to linear modelling, everyone seemed to benefit from the refresher and those who struggled with coding (like me) managed to keep up. In fact although I felt like I was the least competent of the students on the course, at no time did I feel I was holding anyone back.

The facilities at SCENE on Loch Lomond were not luxurious but comfortable; I enjoyed the home style meals and the social evenings. Being quite isolated meant we could concentrate on the work with minimal distractions – apart from the view out of the windows in the lecture theatre through the trees and over the lake when the sun came out, which was quite stunning.

The course was very well organised, from transport to and from the station, to dietary considerations, small walking tours during the breaks and an evening out at the “local” pub, the attention given to making the week comfortable and enjoyable for each individual facilitated the over-all learning experience.

I thoroughly enjoyed the course and came away reasonably competent in using R for linear modelling. And thanks to the tuition focusing on learning good methodology in using R (particularly managing and annotating code) rather than simply applying R to specific statistical problems, I have been able to apply my skills to other statistical techniques.”

Chester Sands
Molecular Ecologist, British Antarctic Survey

10 Students
10 different institutes
8 different countries

Arhus University (Denmark)

Bern University (Switzerland)

Centre for Ecology and Hydrology (CEH) (Scotland)

Glasgow University (Scotland)

ICARUS Maynooth University (Ireland)

Liège University (Belgium)

Macquarie University (Australia)

Oldenburg University

Southampton University (England)

Vetmeduni Vienna (Austria)