In this class we will consider the role of uncertainty in decision - making about renewable natural resources. Students will be introduced to Structured Decision Making (SDM) and Adaptive Management (a special case of SDM), and to quantitative methods associated with them. You will learn about the importance of models and of effective stakeholder engagement to inform good decisions.
This is a non-credit and online course. The purpose of this class is to introduce students to the principles of programming using the R and RStudio software packages. R and RStudio are powerful and versatile data analysis packages that are freely available. While the class focus is on programming in R and RStudio, the programming skills taught are designed so that students can transfer their skills to other programming platforms like ADMB or C. This class replaces R Essentials for Natural Resource Professionals.
This non-credit, on-line course will introduce students to model fitting by maximum likelihood techniques, estimation of uncertainty in model estimates (e.g., likelihood profiling), and methods of inference using multiple models (e.g., AIC model averaging).