NRES 746 - Advanced Analysis Methods in Natural Resources

(3 units)

Applied use and interpretation of multivariate and modeling techniques for natural resources and biological studies.

Grading Basis: Graded
Units of Lecture: 2
Units of Laboratory/Studio: 1
Offered: Every Fall - Even Years

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. identify and contrast the major classes of statistical models used by ecologists (e.g., Bayesian vs frequentist, likelihood-based, machine learning) and explain how and why ecologists use these models.
2. apply analysis tools such as Generalized Linear Models (GLM), Bayesian inference, and Random Forest (RF) on diverse data sets representative of those commonly considered in observational studies in ecology.
3. explore data sets quantitatively and graphically and to prepare data appropriately for analysis.
4. perform statistical analysis, data visualization, simulation modeling, model validation and programming with the statistical computing language R.
5. critically evaluate the strength of inferences drawn from statistical models by understanding and testing major assumptions and using tools such as cross-validation.
6. communicate statistical and computational concepts by leading lectures and discussion on advanced topics in data analysis.

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