Applied R Training for Marine Mammal Researchers
23–27 March 2026 | Live Online
Marine mammal researchers are often tasked with answering causal questions from complex ecological data: How does shipping noise affect whale behaviour? Do management interventions reduce bycatch risk? How will changing ocean temperatures influence survival or distribution? Addressing these questions requires methods that go beyond correlation.
Causal Inference for Ecologists is a five-day, applied R course designed to identify and estimate causal effects using both experimental and observational data. The course provides a practical framework for determining when causal questions can be answered with available data—and how to model them appropriately.
Construct and interpret Directed Acyclic Graphs (DAGs) to formalise causal assumptions.
Identify and avoid bias arising from confounders, colliders, and inappropriate conditioning
Understand why common model selection approaches (e.g. AIC) can be misleading for causal inference
Apply causal inference principles to real-world problems
The live online format combines short lectures with hands-on coding exercises and discussion. All sessions are recorded and available to participants across time zones.
This course is aimed at quantitative scientists with experience in R who are testing hypotheses, estimating causal effects, or developing predictive models from ecological data.
We will work in R using lme4 and rstanarm, covering both frequentist and Bayesian modelling approaches commonly used in marine mammal research.
Secure your place and strengthen the causal foundations of your research.
Register at: https://prstats.org/course/causal-inference-for-ecologists-cife01/
For enquiries, email oliver@prstats.org