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Introduction to GLMs in R for Ecology

GLMs in R for Ecology
  • Level(s) of study: Professional / Short course
  • Study mode(s): Short course
  • Location: Brackenhurst Campus
  • Course duration: 2 days

The way statistics are used in biology, and especially ecology, is changing, with a shift from statistical tests of significance to fitting statistical models to data to explain causation and draw inferences to wider situations. And a new enlightened Bayesian world of statistical inference is also emerging.

An understanding of statistical modelling is no longer a luxury, and it is an expectation that postgraduates and post-doctoral researchers, as well as ecological practitioners possess an understanding of this approach. This change has been unleashed by an explosion in computing power and the advent of powerful and flexible software, such as R, that permits users to wrangle, analyse and visualise their data in novel ways.

This specialist short course is aimed at introducing researchers to analysing ecological and environmental data with GLMs using R. Study design will be discussed, as well as data analysis and statistical interpretation. Sessions will be a blend of interactive demonstrations and lectures, where learners will have the opportunity to ask questions throughout.

Please email us to register your interest in upcoming dates for this course.

What you'll study

On this course you will learn about:

  • Data import, and exploration techniques, including tips to avoid the common pitfalls in tackling a data analysis
  • Recognising common problems associated with analysis of ecological data and how to address them
  • Understanding and applying alternative approaches to model selection
  • Applying statistical modelling methods to ecological data using GLMs

How you’re taught

This course will be delivered fully online using Microsoft Teams.

Regular screen breaks will be included throughout the course.

Please note that this course will not be recorded, so you will need to be available to attend on specified dates and times.

You will be emailed access instructions and a web link to directly enter the online course from, which can be either be viewed in a web browser or within the Microsoft Teams app if you already have this installed.

Prior to the course, learners will be invited to submit their own data, which may be used as examples in the workshop. Whilst we may not be able to use all of the data received, the owners of the selected data sets will be provided with R-code for completing a full analysis of the data and producing publication-quality figures.

What you'll gain

By the end of the course, you will have the ability to import your data to R, undertake a comprehensive data exploration, fit an appropriate statistical model to data and perform model validation and visualisation.

If you attend more than 80% of the course, you will be sent via email a Certificate of Attendance in a PDF format.

Tutor profile

Carl Smith is currently Professor of Natural History at Nottingham Trent University, and holds research positions at the University of Lodz in Poland and the Institute of Vertebrate Biology of the Czech Academy of Sciences. He was formerly Reader in Zoology at the University of St Andrews and held lectureships at the University of Leicester and Queen Mary College of the University of London. Before his first lectureship he held a post-doctoral fellowship at the University of East Anglia, served as a VSO volunteer in Bangladesh and worked for the Food and Agriculture Organisation of the United Nations. He completed a PhD on fish ecology at the University of Aberystwyth.

Mark Warren is currently the national lead for Data Science at the Environment Agency in England. He has worked for the EA for over 18 years on ecological and data led projects. A graduate of the University of East Anglia, Mark holds a PhD from the University of St Andrews on modelling salmonid fish abundance. He has designed ecological river monitoring networks and carried out data analyses to provide evidence-based decision making for water industry regulation. He regularly collaborates with NGOs, water companies, Defra departments, the agricultural sector and academics, among others, providing advice on data collection, statistical analysis, reporting, journal publications and policy. Prior to working at the EA, Mark worked for the National Trust and an ecological consultancy.

Both short-course tutors have co-authored ecological research papers together as well as two statistics books.

Assessment methods

There is no assessment, but a certificate of attendance will be provided for participants who attend at least 80% of the course.

Entry requirements

Prior to attending this course learners should:

  • have a basic knowledge of statistics
  • have basic experience with using R statistical software

To participate in this online course you will need access to R and RStudio, which are both available as free downloads. Prior to the course, you will receive R script and datasets and a list of R packages to install.

How to apply

Please email us to register your interest in upcoming dates for this course.

Please read our notes on the University's commitment to delivering the educational services advertised.

Fees and funding


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