ENST 222 - Environmental Data Analysis and Visualization

Credit Hours: 4
Frequency of Offering: Offered in alternate years, usually in the spring semester

With no prior programming experience required, this course introduces students to in-demand environmental data analysis such as data wrangling and visualization, exploratory data analysis, statistical modeling, version control and collaboration, and reproducible workflows. We will do all of this using R, one of the most popular statistical programming languages in the environmental field. Students cannot receive credit for both this and the marine science course of the same title. This course fulfills the Toolkit requirement in the ENST major.

Prerequisite(s): Prerequisite is successful completion of ENST 100 and ENST 250.