Global Change Science Analytics with R taught by Dr. Matthew R. Helmus is an interdisciplinary course that provides an overview of how researchers use data to solve global problems such as climate change, mass extinction, pandemics, and poverty. Students explore interdisciplinary data, from economics to public health, and learn a marketable skill: communicating data with R, an intuitive statistical computer language. The course is project-based, no prior coding experience is necessary, and no tests are given. Instead, assessment is on project progress and communication of a global change problem of their choice. The most successful students leave class with the quantitative skills to go out and solve our most pressing problems. All majors are welcome!
Below are the final projects produced by students who took the course. These examples span the range of R techniques learned and ideas explored. Before this class, most of these students never had training in R or computer programing.
Example Final Undergraduate Projects
Distribution of street trees in Philadelphia, PA
Adverse Childhood Experiences: A Mid-Atlantic Investigation
A Comprehensive Breakdown of the Education Budget across US States and the Factors that Influence It
The Spread and Prevalence of Bd in American Amphibians
Investigating Factors Impacting Childhood Mortality Rates in the ASEAN Region
Determining the Correlation between Pesticide Usage, Children’s Health, and Income in California
Example Final Graduate Projects (all are related to their thesis work)
Detecting species interactions with machine learning APIs: expanding the hotdog/nothotdog paradigm?
Limb Autotomy Effects on Spider Gait and Running Performance
More propagules, more invaders? Biofouling and ship-borne introductions in the Pacific coast