Envirnmntl Data to Lead Change

1.5 Credits · Level: Graduate

This course focuses on developing the quantitative skills necessary for identifying and analyzing socioenvironmental science data. Using a hands-on, experiential, problem-based approach with real socioenvironmental data, students learn basic methods to build and manage databases. They also study the basics of descriptive and inferential statistical methods, including exploratory data analyses, and basic linear and logistic regressions. Introductions to multivariate analysis and model selection complement the development of analytical skills. The course provides students with experience in the application of statistical methods and the use of open-source statistical software, R. Students also learn the importance of using such analytics to lead change in the context of an original research project and for the Capstone. The emphasis for this course is on drawing meaningful inferences from data using analytical tools; inferences which can then be applied to spark action.