Course Deadline Approaching: Generalized Linear and Mixed Models in R (ONLINE)

[NZCBI-SCBI Training]

The application deadline (Nov 21) is fast approaching for the first of our 2024 course offerings at the Smithsonian-Mason School of Conservation. We do expect this course to fill to capacity before the application deadline, so we encourage anyone interested to apply and register as soon as possible to secure your seat. Remember that only registration (not course acceptance) guarantees your place in the course. Scholarships are available for applicants of less-developed nations. Just tick the relevant box in your application and if you are eligible you will be considered. You statement of interest will be considered a major factor in your scholarship application review.

 

Generalized Linear and Mixed Models in Ecology and Conservation Biology - ONLINE

Dates: Jan 16 – March 10, 2024

Website: https://smconservation.gmu.edu/programs/graduate-and-professional/glm_ecology-ol/

Cost: 500.00 USD (limited scholarships available for citizens of less-developed countries)

Deadline: November 21, 2023

 

Description: This course provides an overview of modern regression-based statistical analysis techniques relevant to ecological research and applied conservation, starting with basic linear models and moving quickly to generalized linear models (GLMs) and mixed models. The course aims to provide a robust understanding of the wide range of regression approaches available, the assumptions associated with each, and the circumstances under which each should be applied. Models covered enjoy widespread use in ecology and conservation biology and can be applied to a huge diversity of data types, study designs, and research questions. Emphasis is placed not only on proper implementation of models, but also on interpretation and explanation of results, recognizing uncertainty, and model limitations. Participants will conduct all exercises using R, a free software environment for statistical computing and graphics which has now become the standard in this field. All exercises and demos will use real ecological data sets and participants will complete an independent analysis project on a unique assigned dataset during the last week of the course. Some basic familiarity with R is recommended before attending.

 

Format: This course is taught in an asynchronous format over 8 weeks, with 2 weekly opportunities for live feedback and instructor interaction over Zoom. Our new format allows for maximum flexibility for participants juggling complicated work schedules, classes and other commitments. This course is available for professional training, but can also be taken for 3 graduate credits at additional cost through George Mason University.