Data Wrangling in R for Ecologists

Course Description

Data are essential to the study of ecology and the environment. Big data (such as data generated by satellites orbiting Earth, billions of biological specimens in natural history museums, and thousands of wildlife camera photographs, to name a few) are disrupting a wide range of industries from human health and environmental monitoring to conservation and government policy. The explosion of data is providing unprecedented opportunities for new discovery and applications, as a result, computational skills to work with data are in high demand: entering data without errors, storing it in a usable and transparent way, extracting key aspects of the data for analysis, and creating accessible visual representations of large and complex datasets. This course will introduce fundamental data skills with an emphasis on environmental and ecological datasets, class will typically consist of short introductions or question and answer sessions, followed by hands on exercises. The course will be taught using R (a popular programming language) and other data tools. No background in programming or data skills is required.

Code

RNR 537

Credits

3

Subject

Renewable Natural Resources