This course discusses the use of statistical techniques in the environmental and agricultural sciences through demonstrations of experiment design, data treatments, statistical tests, error analysis, and statistical bias/assumptions. This course introduces the R coding language, and laboratory exercises focus on using R Studio for data analysis, statistical testing, and data visualization. Lecture, 2.5 hours per week; laboratory, 2 hours per week. 4 credits.