FREE - Introduction to Generalised Linear Models for Ecologists (FGLM01) https://www.prstats.org/course/free-introduction-to-generalised-linear-model... *Free, one-day live online course — 12 August 2025* Offered by PR Statistics, primarily for ecologists and related researchers Course Overview This 4-hour online workshop provides an accessible and practical introduction to Generalised Linear Models (GLMs) using R. It covers core statistical concepts and model fitting for binary and count data, including logistic regression, Poisson and negative binomial models, and link functions. Participants will gain hands-on experience fitting GLMs in R during the session. ------------------------------ Topics Covered - Key theoretical foundations of GLMs - Selecting suitable error distributions and link functions - Fitting and interpreting binary logistic regression and Poisson GLMs in R - Practical workflows for model selection, diagnostics, and interpretation - Application of GLMs to ecological research questions ------------------------------ Technical Requirements - Installation of R and RStudio prior to the session (free and compatible with Windows, macOS, and Linux) - Webcam recommended to support engagement during interactive components - Multi-monitor setup optional but helpful for simultaneous viewing of materials and R environment ------------------------------ Intended Audience This course is designed for ecologists, postgraduate researchers, early-career data analysts, and anyone familiar with basic R usage (e.g. importing data, simple statistics). No prior knowledge of GLMs required; the workshop serves as a foundational introduction to statistical modelling for non-normal datasets. Cost & Registration - *Free of charge* — secure your place via PR Statistics’ site. Spaces are limited and filled on a first-come-first-served basis Join us for this free introduction to GLMs and build the statistical foundations to model binary and count data confidently using R. Register early to reserve your place! -- Oliver Hooker PhD. PR stats