This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – Eastern Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email firstname.lastname@example.org for full details or to discuss how we can accommodate you).
This community analytics course is designed for students who have recently started their projects or researchers who are starting using the R ecosystem. During this three-day course, we will cover the basic concepts of multivariate analysis and their implementation in R. This course is a complement to the PR Statistic offering allowing also beginners and non-programmers to discover the statistical tools needed to analyze an ecological dataset in research, natural resource management or conservation context. This course is not geared toward any particular taxonomic group or ecological system.
We will cover diversity indices, distance measures and multivariate distance-based methods, clustering, classification, and ordination techniques. We will focus on the concept of the methods and their implementation on R using different R packages. We will use real-world examples to implement analyses, such as describing patterns along gradients of environmental or anthropogenic disturbances, quantifying the effects of continuous and discrete predictors, data mining. The course will consist of lectures, work on R code scripts, and exercises for participants.
Any researchers (PhD and MSc students, post-docs, primary investigators) and environmental professionals who are interested in learning multivariate statistics.
Time Zone – Eastern Standard Time
Availability – 20 places
Duration – 3 days
Contact hours – Approx. 21 hours
ECT’s – Equal to 2 ECT’s
Language – English
The course will be divided into theoretical lectures to introduce and explain key concepts and theories, and practices with workshop sessions on R.
~2 modules per day, each module consists of ~1h30/2h lecture + coding, break, ~1h30/2h exercises + summary/discussion.
The schedule can be slightly modified according to the interest of the participants.
The course will take place online. All the sessions will be video recorded and made available immediately on a private video hosting website as soon as possible after each 2hr session.
A basic knowledge of statistics is required.
The participants are required to have some previous experience with R and should know the main data types and how to run commands to create basic plots.
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers.
Participants should be able to install additional software on their own computer during the course (please make sure you have administration rights to your computer).
A large monitor and a second screen, although not absolutely necessary, could improve the learning experience. Participants are also encouraged to keep their webcam active to increase the interaction with the instructor and other students.
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
Monday 29th – Classes from 09:00-17:00
Introduction with participants
Introduction to community ecology
Good practice in programming in R
Data transformation and distance
Tuesday 30th – Classes from 09:00-17:00
Wednesday 31st – Classes from 09:00-17:00
Workshop and practices
Works at – University of Helsink
Teaches – Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03)
Antoine is a plant community ecologist working as a postdoctoral researcher at the University of Helsinki and as a postdoctoral fellow at the Institute of Botany of the Academy of the Czech Republic. Antoine holds a degree in Conservation Biology from the University of Paris-Sud-Orsay, and from the Natural History Museum of Paris, he obtained his PhD in Biology/Ecology from the University of Sherbrooke (Canada). Antoine’s research focuses on the temporal dynamics of biodiversity with a particular focus on the forest and Arctic vegetation. Antoine has taught community ecology, plant ecology and evolution, linear and multivariate statistics assisted on R.