Introduction to reproducible data science in R, including how to import, tidy, visualize, analyze, and communicate Earth and environmental science data and how to apply statistical methods, including bootstrapping, hypothesis testing, and modeling. Course Information: Extensive computer use required. Prior background in coding, statistics, or calculus is not required. Prerequisite(s): Consent of the instructor. Recommended background: Introductory Chemistry, Biology, Earth Science, and/or Environmental Science. Class Schedule Information: To be properly registered, students must enroll in one Lecture-Discussion and one Laboratory.