The micro-credential in Environmental Research & Data Analysis prepares students with advanced technical skills in research methods and data analysis in the environmental sciences broadly. Courses emphasize advanced statistical analysis, field methodology, and computer modeling for use in natural resource management, field research, and geospatial data management.
(3-4 courses recommended)
Pre-req: MTH 243: Introduction to Statistics (pre-requisite for other classes) – 4 credits
ES 330: Environmental Field Methods – 4 credits
ES 386: Environmental Data Analysis – 5 credits
ES 349: Maps, Cartography, and Geospatial Technology – 5 credits
ES 475: Environmental Modeling – 4 credits
Students will be required to earn a minimum of a C- in all courses taken in advancement of the micro-credential.
Design and implement environmental research methods to address environmental research questions in the natural sciences, earth sciences, and social sciences.
Display, interpret and analyze environmental data using statistical analysis software.
Display, interpret and analyze geospatial data using ESRI and open source products.
Develop proficiency in data modeling through the use of STELLA programming systems.