Learn how to analyse ecological survey data while accounting for imperfect detection in our live online course *Analysing Ecological Data with Detection Error (AEDD01)*. https://prstats.org/course/analysing-ecological-data-with-detection-error-aedd01/ Many ecological datasets include detection bias ? species are present but not observed, counts are underestimated, or survey methods vary in detectability. This applied R course provides a practical introduction to statistical methods that explicitly model detection error, helping you produce more accurate and defensible ecological inferences. The course covers: - Understanding detection probability and observation bias in ecological surveys - Occupancy models and abundance models with imperfect detection - Survey design considerations and data requirements - Model fitting, validation, and interpretation in R - Applying detection-error methods to real ecological datasets Delivered live online with recordings available, participants receive course materials, datasets, and post-course support. *Course details* Format: Live online Duration: 2 days Includes: Course materials, code examples, and post-course support This course is suitable for postgraduate students, researchers, ecological consultants, and conservation practitioners working with survey, monitoring, or citizen-science datasets where detectability is uncertain or variable. Full details and registration: https://prstats.org/course/analysing-ecological-data-with-detection-error-aedd01/ Email oliver at prstats.org with any questions.
Oliver Hooker PhD. PR stats [[alternative HTML version deleted]]