Explore tools and best practices for working with large environmental datasets primarily using the programming language R. Cover technical topics like: data types, file management, iteration, functional programming, debugging, code management and collaboration with git and GitHub. Use these tools to analyze environmental data using statistical approaches like: linear models, trend analysis, simple machine learning techniques.
Prerequisite
STAT 158 (Introduction to R Programming or STAT 301)
Instructors
