ONLINE COURSE: MODEL AVERAGING IN ECOLOGY

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ONLINE COURSE: MODEL AVERAGING IN ECOLOGY

Postby jeff.stetz » Fri Oct 25, 2024 3:50 pm

MODEL AVERAGING IN ECOLOGY COURSE DESCRIPTION - Much of statistical practice is concerned with parameter uncertainty, and ignores model uncertainty, which arises when we fit several models and find that no single model stands out as best. This course will provide you with the tools to be able to allow for both types of uncertainty. Model averaging involves estimating the parameters in a way that allows for model uncertainty, and it often provides better estimates and confidence/credible intervals than those from a single best model. The course is divided into two modules (Bayesian and Frequentist model averaging) composed of pre-recorded lecture material and hands-on exercises using R. The course is based on David Fletcher's recent book (Springer 2018), which can be found here.

DATES - December 2, 2024 to February 23, 2025

COST - early bird ends Nov 4th - save $75
No instructor support: starts at $375 professional / $275 student
Instructor support: $525 professional / $425 student

LEARN MORE & REGISTER
https://www.centerforwildlifestudies.or ... ng-ecology

CWS also offers a professional certificate in Applied Quantitative Ecology.

All courses in this program are graduate level and are designed for full-time researchers, graduate students, environmental consultants, conservation specialists, and resource management practitioners. Taught by leading experts in their fields, participants will learn job-ready skills, including how to properly design field studies and controlled experiments, organize and visualize data, and become proficient in a variety of statistical analyses and modeling techniques to answer important environmental questions.

To learn more and apply, please visit: https://www.centerforwildlifestudies.or ... ve-ecology

CENTER FOR WILDLIFE STUDIES is a 501(c)(3) non-profit organization whose global mission is to provide accessible environmental education and promote wildlife conservation through science.
jeff.stetz
 
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