Bayesian Multilevel Modelling using *brms* for Ecologists (BMME01)A Live Online Course for Ecologists & Marine Mammal Researchers *Delivered by PR Stats — October 20–31, 2025* ------------------------------ Understand complex ecological data — even without perfect replication Bayesian multilevel models allow you to robustly analyse data that are hierarchical, sparse, or structured across space and time — exactly the kind of data challenges often faced in *marine mammal science*. In this 10-session live online course, you’ll learn how to build and interpret *Bayesian GLMs and hierarchical models*using the brms package in R. While the course uses general ecological datasets, the concepts and tools are *directly transferable to marine mammal research*, including: - Photo-ID data - Population monitoring - Acoustic detections - Habitat models - Movement and telemetry datasets ------------------------------ Why it’s useful for Marine Mammal Researchers Marine mammal data often suffer from: - *Small sample sizes* or uneven survey effort - *Hierarchical structure* (e.g. sightings nested within individuals, seasons, sites) - *Spatial/temporal autocorrelation* - *Zero-inflation* (e.g. in acoustic or sightings data) Bayesian multilevel models offer an intuitive and principled way to handle these realities — providing *transparent uncertainty quantification* and *flexible model structures* tailored to your study design. ------------------------------ What You’ll Learn Through real-time coding and interactive sessions, you will: - Understand *Bayesian inference* concepts like priors, posteriors, and credible intervals - Fit *GLMs and multilevel/hierarchical models* using brms (Bayesian syntax with R and Stan backend) - Use *informative priors* in ecologically meaningful ways - Apply *model diagnostics and comparison* (WAIC, LOO-CV) - Model *non-Gaussian data* (counts, proportions, zero-inflation) - Handle *spatial and temporal structure* - Understand basics of *joint species distribution models* - Interpret results with uncertainty and communicate findings effectively *Note*: All examples use general ecological datasets — not marine mammal data — but skills are easily adapted. ------------------------------ Course Format & Details Feature Details *Dates* October 20–24 & 27–31, 2025 *Duration* 10 days × ~4 hours per day (total 40 hours) *Time zone* UK time (GMT+1); suitable for EU/UK, and recordings support flexibility *Format* Live, interactive sessions via online platform *Software* R, RStudio, brms (Stan-based Bayesian models) *Skill level* Comfortable with R, basic stats (GLMs, regression, data wrangling) All sessions are recorded, with materials (slides, code, data) provided after each class. ------------------------------ 💰 Course Fees - *Early-bird rate (first 10 places)*: £400 - *Standard rate*: £450 ------------------------------ Is This For You? If you’re a *marine mammal scientist*, *PhD student*, *postdoc*, or *government/NGO researcher* working with: - Sighting or survey data - Mark-recapture or occupancy models - Acoustic presence/absence - Habitat or distribution models - Individual- or group-level data …this course will provide the *Bayesian modelling foundation* you need, even if the example datasets aren’t marine-mammal-specific. ------------------------------ Learn to model your marine mammal data with more clarity, flexibility, and statistical confidence. *Register now to secure your early-bird place* and bring advanced Bayesian tools to your ecological research toolkit. Email oliver@prstats.org with any questions. -- Oliver Hooker PhD. PR stats