Introduction to Generalised Linear Models for Ecologists
Master the fundamentals of Generalised Linear Models in R.
https://www.prstats.org/course/introduction-to-generalised-linear-models-for-ecologists-glme01/
Why this course? Traditional introductory statistics often treat t tests,
ANOVA and regression as disconnected procedures. GLMs, on the other hand,
offer a unified, flexible framework to model a wide range of ecological
data?from continuous measurements to binary and count outcomes.
Duration:
10 Days, 4 hours per day
Next Date:
8th ? 12 & 15th ? 19th September 2025
Format:
Live Online Format
Cost:
First 10 places ?400
Normal price ?450
Course Description
This 10-day course provides a comprehensive introduction to Generalised
Linear Models (GLMs) using the R programming language. GLMs are a powerful
extension of linear models that allow for response variables with error
distributions other than the normal distribution, such as binary, count, or
proportion data. Through a mix of lectures and practical exercises, this
course introduces GLM theory and walks participants through data
preparation, model fitting, diagnostics, interpretation, and visualisation.
Each session focuses on a key GLM type, such as logistic regression or
Poisson regression, using ecological datasets. No prior experience with
GLMs is required, but basic familiarity with R and linear models is
recommended. The course is suited to researchers, analysts, and students
who want to build a strong foundation in applied statistical modelling.
What You?ll Learn
? The theoretical foundations of Generalised Linear Models (GLMs),
? How to choose appropriate error structures and link functions,
? How to fit logistic, Poisson, and other GLMs in R,
? Techniques for model selection and checking model assumptions,
? How to interpret model coefficients and assess goodness of fit,
? Visualising and communicating model results effectively,
? Common pitfalls and how to avoid them when using GLMs,
? How to apply GLMs to real-world problems.
Please email oliverhooker at prstatistics.com with any questions.
--
Oliver Hooker PhD.
PR stats
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