The open-source R programming language is widely used by environmental professionals and researchers at state agencies, NGO’s, and colleges and universities. Students will learn how to import, clean, manage, and process data in both "base R" and using functions from the "tidyverse" collection of packages. Students will primarily use plotting functions from "ggplot2" to create meaningful visualizations. Students will have the choice to use R for introductory-level statistical analyses (including correlation, simple linear regression, and chi-squared test of independence), OR for more advanced analyses and approaches including model selection, mixed effects modeling, and Bayesian data analysis. In-person activities will include lectures, workshops, and hands-on computer assignments in the Computer Applications Lab. Full remote participation by Zoom and using R (through R Studio) on CAL computers or a student’s own computer is also possible.
Prerequisite: You must be comfortable setting up your working directory, importing data from .csv files, and downloading and installing packages in R, using the R Studio environment. Tutorials can be provided for practice with these skills before the first day of class. Undergraduate enrollment permitted with faculty permission.
John Withey(MES Core Faculty) is a terrestrial ecologist with a background in field ornithology, who first learned R programming as a graduate student more than 20 years ago. He has written R code to estimate spring arrival dates of migratory birds, assess conservation return-on-investment and account for evolutionary distinctiveness, and to incorporate climate change projections into planning for U.S. protected areas. He enjoys using a combination of field-based empirical data, ecological modeling, and spatial and quantitative analyses in his work.
Hi-Flex Class Format: This course is offered in a “Hi-Flex” format. Students can attend fully in-person, fully online, or a mix of both. Each class will be offered in-person but will also include a zoom link for remote attendees. We will do our best to provide comparable experiences for both in-person and remote students.
CLASS SCHEDULE: First Summer Session, Tuesday and Thursday nights, 6-10pm